GGUF fix
This is the same model as cognitivecomputations/dolphin-2.9.1-dbrx, but with gguf fixes made by Kenjoyer applied(thanks a lot!). This model can be converted into gguf using llama.cpp.
Benchmarks and personal opinion
NeoEvalPlusN_benchmark
Name | Quant | Size | B | C | D | S | P | total | BCD | SP |
---|---|---|---|---|---|---|---|---|---|---|
cognitivecomputations/dolphin-2.9.1-dbrx | Q6_K | 16x12B | 3 | 1 | 3 | 4 | 6 | 17 | 7 | 10 |
cognitivecomputations/dolphin-2.9.1-qwen-110b | Q6_K | 110B | 0 | 1 | 3 | 3.75 | 4.25 | 12 | 4 | 8 |
databricks/dbrx-instruct | Q6_K | 16x12B | 0 | 0 | 0 | 6.5 | 4.5 | 11 | 0 | 11 |
cognitivecomputations/dolphin-2.2-70b | Q6_K | 70B | 0 | 1 | 1 | 4.5 | 4.5 | 11 | 2 | 9 |
Maximum | n/a | n/a | 3 | 2 | 3 | 8 | 6 | 22 | 8 | 14 |
More compliant than the official instruct tune(BCD). To my surprise, performed much better overall than qwen-110b tuned on the same dataset. Wrote 6 perfect poems(P column), which is very unusual. Only models from goliath family and more recent llama-3-70b-instruct could do that. Stylized writing tests(S column) were a bit disappointing, Dolphin is not famous for that. In practical use, did perform better than the official tune. Still knows a lot, just like the official tune. Writing is not great, wouldn't use it over Command-r+, unless I need to know some obscure facts. Feels like quantization hurts it a lot more than dense models.
Verdict: Meh, just like the other dolphins. Eric, no disrespect, but you need to get better datasets. GPTslop really hurts practical performance of the model.
Original model card below
Dolphin 2.9.1 DBRX 🐬
Curated and trained by Eric Hartford, Lucas Atkins, and Fernando Fernandes, and Cognitive Computations
Discord: https://discord.gg/cognitivecomputations
Our appreciation for the sponsors of Dolphin 2.9.1:
- Crusoe Cloud - provided excellent on-demand 8xH100 node
This model is based on databricks/dbrx-base, and is governed by databricks-open-model-license
The base model has 32k context, and the full-weight fine-tuning was with 4k sequence length.
This model was trained FFT on parameters selected by Laser Scanner, using ChatML prompt template format.
example:
<|im_start|>system
You are Dolphin, a helpful AI assistant.<|im_end|>
<|im_start|>user
{prompt}<|im_end|>
<|im_start|>assistant
Dolphin-2.9.1 has a variety of instruction, conversational, and coding skills. It also has initial agentic abilities and supports function calling.
Dolphin is uncensored. We have filtered the dataset to remove alignment and bias. This makes the model more compliant. You are advised to implement your own alignment layer before exposing the model as a service. It will be highly compliant with any requests, even unethical ones. Please read my blog post about uncensored models. https://erichartford.com/uncensored-models You are responsible for any content you create using this model. Enjoy responsibly.
Dolphin is licensed according to Meta's Llama license. We grant permission for any use, including commercial, that falls within accordance with Meta's Llama-3 license. Dolphin was trained on data generated from GPT4, among other models.
Evals
Training
See axolotl config
axolotl version: 0.4.0
base_model: /workspace/axolotl/dbrx-checkpoint
model_type: AutoModelForCausalLM
tokenizer_type: AutoTokenizer
trust_remote_code: true
load_in_8bit: false
# load_in_4bit: true
strict: false
# adapter: qlora
# lora_modules_to_save: [embed_tokens, lm_head]
# lora_r: 32
# lora_alpha: 16
# lora_dropout: 0.05
# lora_target_linear: false
# lora_fan_in_fan_out:
datasets:
- path: /workspace/datasets/dolphin-2.9/dolphin201-sharegpt2.jsonl
type: sharegpt
conversation: chatml
# - path: /workspace/datasets/dolphin-2.9/Ultrachat200kunfiltered.jsonl
# type: sharegpt
# conversation: chatml
- path: /workspace/datasets/dolphin-2.9/dolphin-coder-translate-sharegpt2.jsonl
type: sharegpt
conversation: chatml
- path: /workspace/datasets/dolphin-2.9/dolphin-coder-codegen-sharegpt2.jsonl
type: sharegpt
conversation: chatml
- path: /workspace/datasets/dolphin-2.9/m-a-p_Code-Feedback-sharegpt-unfiltered.jsonl
type: sharegpt
conversation: chatml
- path: /workspace/datasets/dolphin-2.9/m-a-p_CodeFeedback-Filtered-Instruction-sharegpt-unfiltered.jsonl
type: sharegpt
conversation: chatml
- path: /workspace/datasets/dolphin-2.9/not_samantha_norefusals.jsonl
type: sharegpt
conversation: chatml
- path: /workspace/datasets/dolphin-2.9/Orca-Math-resort-unfiltered.jsonl
type: sharegpt
conversation: chatml
- path: /workspace/datasets/dolphin-2.9/agent_instruct_react_unfiltered.jsonl
type: sharegpt
conversation: chatml
- path: /workspace/datasets/dolphin-2.9/toolbench_instruct_j1s1_3k_unfiltered.jsonl
type: sharegpt
conversation: chatml
- path: /workspace/datasets/dolphin-2.9/toolbench_negative_unfiltered.jsonl
type: sharegpt
conversation: chatml
- path: /workspace/datasets/dolphin-2.9/toolbench_react_10p_unfiltered.jsonl
type: sharegpt
conversation: chatml
- path: /workspace/datasets/dolphin-2.9/toolbench_tflan_cot_30p_unfiltered.jsonl
type: sharegpt
conversation: chatml
- path: /workspace/datasets/dolphin-2.9/openhermes200k_unfiltered.jsonl
type: sharegpt
conversation: chatml
# - path: /workspace/datasets/dolphin-2.9/SystemConversations.jsonl
# type: sharegpt
# conversation: chatml
chat_template: chatml
unfrozen_parameters:
- ^lm_head.weight$
# ffn.experts.mlp_experts.0.v1 layers
- transformer.blocks.30.ffn.experts.mlp_experts.0.v1
- transformer.blocks.32.ffn.experts.mlp_experts.0.v1
- transformer.blocks.25.ffn.experts.mlp_experts.0.v1
- transformer.blocks.15.ffn.experts.mlp_experts.0.v1
- transformer.blocks.22.ffn.experts.mlp_experts.0.v1
- transformer.blocks.31.ffn.experts.mlp_experts.0.v1
- transformer.blocks.7.ffn.experts.mlp_experts.0.v1
- transformer.blocks.21.ffn.experts.mlp_experts.0.v1
- transformer.blocks.8.ffn.experts.mlp_experts.0.v1
- transformer.blocks.23.ffn.experts.mlp_experts.0.v1
# ffn.experts.mlp_experts.0.w1 layers
- transformer.blocks.7.ffn.experts.mlp_experts.0.w1
- transformer.blocks.8.ffn.experts.mlp_experts.0.w1
- transformer.blocks.30.ffn.experts.mlp_experts.0.w1
- transformer.blocks.4.ffn.experts.mlp_experts.0.w1
- transformer.blocks.0.ffn.experts.mlp_experts.0.w1
- transformer.blocks.32.ffn.experts.mlp_experts.0.w1
- transformer.blocks.6.ffn.experts.mlp_experts.0.w1
- transformer.blocks.3.ffn.experts.mlp_experts.0.w1
- transformer.blocks.25.ffn.experts.mlp_experts.0.w1
- transformer.blocks.5.ffn.experts.mlp_experts.0.w1
# ffn.experts.mlp_experts.0.w2 layers
- transformer.blocks.25.ffn.experts.mlp_experts.0.w2
- transformer.blocks.22.ffn.experts.mlp_experts.0.w2
- transformer.blocks.27.ffn.experts.mlp_experts.0.w2
- transformer.blocks.26.ffn.experts.mlp_experts.0.w2
- transformer.blocks.4.ffn.experts.mlp_experts.0.w2
- transformer.blocks.29.ffn.experts.mlp_experts.0.w2
- transformer.blocks.32.ffn.experts.mlp_experts.0.w2
- transformer.blocks.5.ffn.experts.mlp_experts.0.w2
- transformer.blocks.7.ffn.experts.mlp_experts.0.w2
- transformer.blocks.3.ffn.experts.mlp_experts.0.w2
# ffn.experts.mlp_experts.1.v1 layers
- transformer.blocks.27.ffn.experts.mlp_experts.1.v1
- transformer.blocks.25.ffn.experts.mlp_experts.1.v1
- transformer.blocks.29.ffn.experts.mlp_experts.1.v1
- transformer.blocks.33.ffn.experts.mlp_experts.1.v1
- transformer.blocks.23.ffn.experts.mlp_experts.1.v1
- transformer.blocks.30.ffn.experts.mlp_experts.1.v1
- transformer.blocks.6.ffn.experts.mlp_experts.1.v1
- transformer.blocks.21.ffn.experts.mlp_experts.1.v1
- transformer.blocks.15.ffn.experts.mlp_experts.1.v1
- transformer.blocks.7.ffn.experts.mlp_experts.1.v1
# ffn.experts.mlp_experts.1.w1 layers
- transformer.blocks.0.ffn.experts.mlp_experts.1.w1
- transformer.blocks.6.ffn.experts.mlp_experts.1.w1
- transformer.blocks.7.ffn.experts.mlp_experts.1.w1
- transformer.blocks.4.ffn.experts.mlp_experts.1.w1
- transformer.blocks.8.ffn.experts.mlp_experts.1.w1
- transformer.blocks.29.ffn.experts.mlp_experts.1.w1
- transformer.blocks.33.ffn.experts.mlp_experts.1.w1
- transformer.blocks.27.ffn.experts.mlp_experts.1.w1
- transformer.blocks.1.ffn.experts.mlp_experts.1.w1
- transformer.blocks.10.ffn.experts.mlp_experts.1.w1
# ffn.experts.mlp_experts.1.w2 layers
- transformer.blocks.25.ffn.experts.mlp_experts.1.w2
- transformer.blocks.23.ffn.experts.mlp_experts.1.w2
- transformer.blocks.27.ffn.experts.mlp_experts.1.w2
- transformer.blocks.29.ffn.experts.mlp_experts.1.w2
- transformer.blocks.31.ffn.experts.mlp_experts.1.w2
- transformer.blocks.4.ffn.experts.mlp_experts.1.w2
- transformer.blocks.32.ffn.experts.mlp_experts.1.w2
- transformer.blocks.30.ffn.experts.mlp_experts.1.w2
- transformer.blocks.21.ffn.experts.mlp_experts.1.w2
- transformer.blocks.33.ffn.experts.mlp_experts.1.w2
# ffn.experts.mlp_experts.10.v1 layers
- transformer.blocks.28.ffn.experts.mlp_experts.10.v1
- transformer.blocks.34.ffn.experts.mlp_experts.10.v1
- transformer.blocks.33.ffn.experts.mlp_experts.10.v1
- transformer.blocks.26.ffn.experts.mlp_experts.10.v1
- transformer.blocks.32.ffn.experts.mlp_experts.10.v1
- transformer.blocks.30.ffn.experts.mlp_experts.10.v1
- transformer.blocks.36.ffn.experts.mlp_experts.10.v1
- transformer.blocks.24.ffn.experts.mlp_experts.10.v1
- transformer.blocks.20.ffn.experts.mlp_experts.10.v1
- transformer.blocks.35.ffn.experts.mlp_experts.10.v1
# ffn.experts.mlp_experts.10.w1 layers
- transformer.blocks.24.ffn.experts.mlp_experts.10.w1
- transformer.blocks.33.ffn.experts.mlp_experts.10.w1
- transformer.blocks.8.ffn.experts.mlp_experts.10.w1
- transformer.blocks.7.ffn.experts.mlp_experts.10.w1
- transformer.blocks.34.ffn.experts.mlp_experts.10.w1
- transformer.blocks.28.ffn.experts.mlp_experts.10.w1
- transformer.blocks.30.ffn.experts.mlp_experts.10.w1
- transformer.blocks.1.ffn.experts.mlp_experts.10.w1
- transformer.blocks.3.ffn.experts.mlp_experts.10.w1
- transformer.blocks.5.ffn.experts.mlp_experts.10.w1
# ffn.experts.mlp_experts.10.w2 layers
- transformer.blocks.24.ffn.experts.mlp_experts.10.w2
- transformer.blocks.28.ffn.experts.mlp_experts.10.w2
- transformer.blocks.23.ffn.experts.mlp_experts.10.w2
- transformer.blocks.30.ffn.experts.mlp_experts.10.w2
- transformer.blocks.32.ffn.experts.mlp_experts.10.w2
- transformer.blocks.3.ffn.experts.mlp_experts.10.w2
- transformer.blocks.33.ffn.experts.mlp_experts.10.w2
- transformer.blocks.26.ffn.experts.mlp_experts.10.w2
- transformer.blocks.2.ffn.experts.mlp_experts.10.w2
- transformer.blocks.20.ffn.experts.mlp_experts.10.w2
# ffn.experts.mlp_experts.11.w1 layers
- transformer.blocks.6.ffn.experts.mlp_experts.11.w1
- transformer.blocks.8.ffn.experts.mlp_experts.11.w1
- transformer.blocks.9.ffn.experts.mlp_experts.11.w1
- transformer.blocks.0.ffn.experts.mlp_experts.11.w1
- transformer.blocks.10.ffn.experts.mlp_experts.11.w1
- transformer.blocks.28.ffn.experts.mlp_experts.11.w1
- transformer.blocks.3.ffn.experts.mlp_experts.11.w1
- transformer.blocks.5.ffn.experts.mlp_experts.11.w1
- transformer.blocks.33.ffn.experts.mlp_experts.11.w1
- transformer.blocks.13.ffn.experts.mlp_experts.11.w1
# ffn.experts.mlp_experts.11.w2 layers
- transformer.blocks.27.ffn.experts.mlp_experts.11.w2
- transformer.blocks.24.ffn.experts.mlp_experts.11.w2
- transformer.blocks.29.ffn.experts.mlp_experts.11.w2
- transformer.blocks.30.ffn.experts.mlp_experts.11.w2
- transformer.blocks.22.ffn.experts.mlp_experts.11.w2
- transformer.blocks.6.ffn.experts.mlp_experts.11.w2
- transformer.blocks.25.ffn.experts.mlp_experts.11.w2
- transformer.blocks.7.ffn.experts.mlp_experts.11.w2
- transformer.blocks.28.ffn.experts.mlp_experts.11.w2
- transformer.blocks.5.ffn.experts.mlp_experts.11.w2
# ffn.experts.mlp_experts.12.v1 layers
- transformer.blocks.30.ffn.experts.mlp_experts.12.v1
- transformer.blocks.21.ffn.experts.mlp_experts.12.v1
- transformer.blocks.27.ffn.experts.mlp_experts.12.v1
- transformer.blocks.28.ffn.experts.mlp_experts.12.v1
- transformer.blocks.29.ffn.experts.mlp_experts.12.v1
- transformer.blocks.8.ffn.experts.mlp_experts.12.v1
- transformer.blocks.10.ffn.experts.mlp_experts.12.v1
- transformer.blocks.23.ffn.experts.mlp_experts.12.v1
- transformer.blocks.6.ffn.experts.mlp_experts.12.v1
- transformer.blocks.20.ffn.experts.mlp_experts.12.v1
# ffn.experts.mlp_experts.12.w1 layers
- transformer.blocks.8.ffn.experts.mlp_experts.12.w1
- transformer.blocks.1.ffn.experts.mlp_experts.12.w1
- transformer.blocks.0.ffn.experts.mlp_experts.12.w1
- transformer.blocks.6.ffn.experts.mlp_experts.12.w1
- transformer.blocks.9.ffn.experts.mlp_experts.12.w1
- transformer.blocks.2.ffn.experts.mlp_experts.12.w1
- transformer.blocks.10.ffn.experts.mlp_experts.12.w1
- transformer.blocks.17.ffn.experts.mlp_experts.12.w1
- transformer.blocks.29.ffn.experts.mlp_experts.12.w1
- transformer.blocks.21.ffn.experts.mlp_experts.12.w1
# ffn.experts.mlp_experts.12.w2 layers
- transformer.blocks.6.ffn.experts.mlp_experts.12.w2
- transformer.blocks.25.ffn.experts.mlp_experts.12.w2
- transformer.blocks.27.ffn.experts.mlp_experts.12.w2
- transformer.blocks.8.ffn.experts.mlp_experts.12.w2
- transformer.blocks.31.ffn.experts.mlp_experts.12.w2
- transformer.blocks.21.ffn.experts.mlp_experts.12.w2
- transformer.blocks.2.ffn.experts.mlp_experts.12.w2
- transformer.blocks.29.ffn.experts.mlp_experts.12.w2
- transformer.blocks.32.ffn.experts.mlp_experts.12.w2
- transformer.blocks.30.ffn.experts.mlp_experts.12.w2
# ffn.experts.mlp_experts.13.v1 layers
- transformer.blocks.31.ffn.experts.mlp_experts.13.v1
- transformer.blocks.24.ffn.experts.mlp_experts.13.v1
- transformer.blocks.30.ffn.experts.mlp_experts.13.v1
- transformer.blocks.29.ffn.experts.mlp_experts.13.v1
- transformer.blocks.8.ffn.experts.mlp_experts.13.v1
- transformer.blocks.10.ffn.experts.mlp_experts.13.v1
- transformer.blocks.11.ffn.experts.mlp_experts.13.v1
- transformer.blocks.27.ffn.experts.mlp_experts.13.v1
- transformer.blocks.25.ffn.experts.mlp_experts.13.v1
- transformer.blocks.36.ffn.experts.mlp_experts.13.v1
# ffn.experts.mlp_experts.13.w1 layers
- transformer.blocks.4.ffn.experts.mlp_experts.13.w1
- transformer.blocks.10.ffn.experts.mlp_experts.13.w1
- transformer.blocks.6.ffn.experts.mlp_experts.13.w1
- transformer.blocks.0.ffn.experts.mlp_experts.13.w1
- transformer.blocks.3.ffn.experts.mlp_experts.13.w1
- transformer.blocks.24.ffn.experts.mlp_experts.13.w1
- transformer.blocks.8.ffn.experts.mlp_experts.13.w1
- transformer.blocks.1.ffn.experts.mlp_experts.13.w1
- transformer.blocks.30.ffn.experts.mlp_experts.13.w1
- transformer.blocks.11.ffn.experts.mlp_experts.13.w1
# ffn.experts.mlp_experts.13.w2 layers
- transformer.blocks.24.ffn.experts.mlp_experts.13.w2
- transformer.blocks.20.ffn.experts.mlp_experts.13.w2
- transformer.blocks.25.ffn.experts.mlp_experts.13.w2
- transformer.blocks.27.ffn.experts.mlp_experts.13.w2
- transformer.blocks.3.ffn.experts.mlp_experts.13.w2
- transformer.blocks.4.ffn.experts.mlp_experts.13.w2
- transformer.blocks.29.ffn.experts.mlp_experts.13.w2
- transformer.blocks.6.ffn.experts.mlp_experts.13.w2
- transformer.blocks.30.ffn.experts.mlp_experts.13.w2
- transformer.blocks.31.ffn.experts.mlp_experts.13.w2
# ffn.experts.mlp_experts.14.v1 layers
- transformer.blocks.28.ffn.experts.mlp_experts.14.v1
- transformer.blocks.26.ffn.experts.mlp_experts.14.v1
- transformer.blocks.29.ffn.experts.mlp_experts.14.v1
- transformer.blocks.35.ffn.experts.mlp_experts.14.v1
- transformer.blocks.24.ffn.experts.mlp_experts.14.v1
- transformer.blocks.8.ffn.experts.mlp_experts.14.v1
- transformer.blocks.32.ffn.experts.mlp_experts.14.v1
- transformer.blocks.15.ffn.experts.mlp_experts.14.v1
- transformer.blocks.11.ffn.experts.mlp_experts.14.v1
- transformer.blocks.22.ffn.experts.mlp_experts.14.v1
# ffn.experts.mlp_experts.14.w1 layers
- transformer.blocks.8.ffn.experts.mlp_experts.14.w1
- transformer.blocks.4.ffn.experts.mlp_experts.14.w1
- transformer.blocks.5.ffn.experts.mlp_experts.14.w1
- transformer.blocks.7.ffn.experts.mlp_experts.14.w1
- transformer.blocks.3.ffn.experts.mlp_experts.14.w1
- transformer.blocks.13.ffn.experts.mlp_experts.14.w1
- transformer.blocks.29.ffn.experts.mlp_experts.14.w1
- transformer.blocks.6.ffn.experts.mlp_experts.14.w1
- transformer.blocks.28.ffn.experts.mlp_experts.14.w1
- transformer.blocks.9.ffn.experts.mlp_experts.14.w1
# ffn.experts.mlp_experts.14.w2 layers
- transformer.blocks.26.ffn.experts.mlp_experts.14.w2
- transformer.blocks.24.ffn.experts.mlp_experts.14.w2
- transformer.blocks.29.ffn.experts.mlp_experts.14.w2
- transformer.blocks.28.ffn.experts.mlp_experts.14.w2
- transformer.blocks.31.ffn.experts.mlp_experts.14.w2
- transformer.blocks.5.ffn.experts.mlp_experts.14.w2
- transformer.blocks.4.ffn.experts.mlp_experts.14.w2
- transformer.blocks.32.ffn.experts.mlp_experts.14.w2
- transformer.blocks.6.ffn.experts.mlp_experts.14.w2
- transformer.blocks.22.ffn.experts.mlp_experts.14.w2
# ffn.experts.mlp_experts.15.v1 layers
- transformer.blocks.33.ffn.experts.mlp_experts.15.v1
- transformer.blocks.26.ffn.experts.mlp_experts.15.v1
- transformer.blocks.31.ffn.experts.mlp_experts.15.v1
- transformer.blocks.28.ffn.experts.mlp_experts.15.v1
- transformer.blocks.9.ffn.experts.mlp_experts.15.v1
- transformer.blocks.34.ffn.experts.mlp_experts.15.v1
- transformer.blocks.29.ffn.experts.mlp_experts.15.v1
- transformer.blocks.7.ffn.experts.mlp_experts.15.v1
- transformer.blocks.17.ffn.experts.mlp_experts.15.v1
- transformer.blocks.15.ffn.experts.mlp_experts.15.v1
# ffn.experts.mlp_experts.15.w1 layers
- transformer.blocks.6.ffn.experts.mlp_experts.15.w1
- transformer.blocks.9.ffn.experts.mlp_experts.15.w1
- transformer.blocks.0.ffn.experts.mlp_experts.15.w1
- transformer.blocks.7.ffn.experts.mlp_experts.15.w1
- transformer.blocks.14.ffn.experts.mlp_experts.15.w1
- transformer.blocks.33.ffn.experts.mlp_experts.15.w1
- transformer.blocks.34.ffn.experts.mlp_experts.15.w1
- transformer.blocks.10.ffn.experts.mlp_experts.15.w1
- transformer.blocks.5.ffn.experts.mlp_experts.15.w1
- transformer.blocks.29.ffn.experts.mlp_experts.15.w1
# ffn.experts.mlp_experts.15.w2 layers
- transformer.blocks.28.ffn.experts.mlp_experts.15.w2
- transformer.blocks.26.ffn.experts.mlp_experts.15.w2
- transformer.blocks.27.ffn.experts.mlp_experts.15.w2
- transformer.blocks.29.ffn.experts.mlp_experts.15.w2
- transformer.blocks.6.ffn.experts.mlp_experts.15.w2
- transformer.blocks.31.ffn.experts.mlp_experts.15.w2
- transformer.blocks.7.ffn.experts.mlp_experts.15.w2
- transformer.blocks.33.ffn.experts.mlp_experts.15.w2
- transformer.blocks.32.ffn.experts.mlp_experts.15.w2
- transformer.blocks.25.ffn.experts.mlp_experts.15.w2
# ffn.experts.mlp_experts.2.v1 layers
- transformer.blocks.31.ffn.experts.mlp_experts.2.v1
- transformer.blocks.27.ffn.experts.mlp_experts.2.v1
- transformer.blocks.28.ffn.experts.mlp_experts.2.v1
- transformer.blocks.30.ffn.experts.mlp_experts.2.v1
- transformer.blocks.23.ffn.experts.mlp_experts.2.v1
- transformer.blocks.32.ffn.experts.mlp_experts.2.v1
- transformer.blocks.35.ffn.experts.mlp_experts.2.v1
- transformer.blocks.7.ffn.experts.mlp_experts.2.v1
- transformer.blocks.21.ffn.experts.mlp_experts.2.v1
- transformer.blocks.15.ffn.experts.mlp_experts.2.v1
# ffn.experts.mlp_experts.2.w1 layers
- transformer.blocks.7.ffn.experts.mlp_experts.2.w1
- transformer.blocks.6.ffn.experts.mlp_experts.2.w1
- transformer.blocks.1.ffn.experts.mlp_experts.2.w1
- transformer.blocks.4.ffn.experts.mlp_experts.2.w1
- transformer.blocks.5.ffn.experts.mlp_experts.2.w1
- transformer.blocks.29.ffn.experts.mlp_experts.2.w1
- transformer.blocks.0.ffn.experts.mlp_experts.2.w1
- transformer.blocks.9.ffn.experts.mlp_experts.2.w1
- transformer.blocks.31.ffn.experts.mlp_experts.2.w1
- transformer.blocks.30.ffn.experts.mlp_experts.2.w1
# ffn.experts.mlp_experts.2.w2 layers
- transformer.blocks.26.ffn.experts.mlp_experts.2.w2
- transformer.blocks.27.ffn.experts.mlp_experts.2.w2
- transformer.blocks.33.ffn.experts.mlp_experts.2.w2
- transformer.blocks.5.ffn.experts.mlp_experts.2.w2
- transformer.blocks.23.ffn.experts.mlp_experts.2.w2
- transformer.blocks.32.ffn.experts.mlp_experts.2.w2
- transformer.blocks.28.ffn.experts.mlp_experts.2.w2
- transformer.blocks.4.ffn.experts.mlp_experts.2.w2
- transformer.blocks.29.ffn.experts.mlp_experts.2.w2
- transformer.blocks.30.ffn.experts.mlp_experts.2.w2
# ffn.experts.mlp_experts.3.v1 layers
- transformer.blocks.28.ffn.experts.mlp_experts.3.v1
- transformer.blocks.33.ffn.experts.mlp_experts.3.v1
- transformer.blocks.36.ffn.experts.mlp_experts.3.v1
- transformer.blocks.29.ffn.experts.mlp_experts.3.v1
- transformer.blocks.30.ffn.experts.mlp_experts.3.v1
- transformer.blocks.7.ffn.experts.mlp_experts.3.v1
- transformer.blocks.14.ffn.experts.mlp_experts.3.v1
- transformer.blocks.10.ffn.experts.mlp_experts.3.v1
- transformer.blocks.31.ffn.experts.mlp_experts.3.v1
- transformer.blocks.21.ffn.experts.mlp_experts.3.v1
# ffn.experts.mlp_experts.3.w1 layers
- transformer.blocks.7.ffn.experts.mlp_experts.3.w1
- transformer.blocks.0.ffn.experts.mlp_experts.3.w1
- transformer.blocks.10.ffn.experts.mlp_experts.3.w1
- transformer.blocks.9.ffn.experts.mlp_experts.3.w1
- transformer.blocks.29.ffn.experts.mlp_experts.3.w1
- transformer.blocks.5.ffn.experts.mlp_experts.3.w1
- transformer.blocks.30.ffn.experts.mlp_experts.3.w1
- transformer.blocks.4.ffn.experts.mlp_experts.3.w1
- transformer.blocks.33.ffn.experts.mlp_experts.3.w1
- transformer.blocks.1.ffn.experts.mlp_experts.3.w1
# ffn.experts.mlp_experts.3.w2 layers
- transformer.blocks.28.ffn.experts.mlp_experts.3.w2
- transformer.blocks.5.ffn.experts.mlp_experts.3.w2
- transformer.blocks.24.ffn.experts.mlp_experts.3.w2
- transformer.blocks.31.ffn.experts.mlp_experts.3.w2
- transformer.blocks.30.ffn.experts.mlp_experts.3.w2
- transformer.blocks.21.ffn.experts.mlp_experts.3.w2
- transformer.blocks.32.ffn.experts.mlp_experts.3.w2
- transformer.blocks.29.ffn.experts.mlp_experts.3.w2
- transformer.blocks.26.ffn.experts.mlp_experts.3.w2
- transformer.blocks.2.ffn.experts.mlp_experts.3.w2
# ffn.experts.mlp_experts.4.v1 layers
- transformer.blocks.34.ffn.experts.mlp_experts.4.v1
- transformer.blocks.31.ffn.experts.mlp_experts.4.v1
- transformer.blocks.26.ffn.experts.mlp_experts.4.v1
- transformer.blocks.24.ffn.experts.mlp_experts.4.v1
- transformer.blocks.14.ffn.experts.mlp_experts.4.v1
- transformer.blocks.32.ffn.experts.mlp_experts.4.v1
- transformer.blocks.7.ffn.experts.mlp_experts.4.v1
- transformer.blocks.6.ffn.experts.mlp_experts.4.v1
- transformer.blocks.20.ffn.experts.mlp_experts.4.v1
- transformer.blocks.9.ffn.experts.mlp_experts.4.v1
# ffn.experts.mlp_experts.4.w1 layers
- transformer.blocks.6.ffn.experts.mlp_experts.4.w1
- transformer.blocks.4.ffn.experts.mlp_experts.4.w1
- transformer.blocks.7.ffn.experts.mlp_experts.4.w1
- transformer.blocks.9.ffn.experts.mlp_experts.4.w1
- transformer.blocks.0.ffn.experts.mlp_experts.4.w1
- transformer.blocks.5.ffn.experts.mlp_experts.4.w1
- transformer.blocks.14.ffn.experts.mlp_experts.4.w1
- transformer.blocks.34.ffn.experts.mlp_experts.4.w1
- transformer.blocks.8.ffn.experts.mlp_experts.4.w1
- transformer.blocks.29.ffn.experts.mlp_experts.4.w1
# ffn.experts.mlp_experts.4.w2 layers
- transformer.blocks.25.ffn.experts.mlp_experts.4.w2
- transformer.blocks.24.ffn.experts.mlp_experts.4.w2
- transformer.blocks.26.ffn.experts.mlp_experts.4.w2
- transformer.blocks.5.ffn.experts.mlp_experts.4.w2
- transformer.blocks.6.ffn.experts.mlp_experts.4.w2
- transformer.blocks.32.ffn.experts.mlp_experts.4.w2
- transformer.blocks.4.ffn.experts.mlp_experts.4.w2
- transformer.blocks.36.ffn.experts.mlp_experts.4.w2
- transformer.blocks.29.ffn.experts.mlp_experts.4.w2
- transformer.blocks.27.ffn.experts.mlp_experts.4.w2
# ffn.experts.mlp_experts.5.v1 layers
- transformer.blocks.35.ffn.experts.mlp_experts.5.v1
- transformer.blocks.30.ffn.experts.mlp_experts.5.v1
- transformer.blocks.28.ffn.experts.mlp_experts.5.v1
- transformer.blocks.32.ffn.experts.mlp_experts.5.v1
- transformer.blocks.27.ffn.experts.mlp_experts.5.v1
- transformer.blocks.26.ffn.experts.mlp_experts.5.v1
- transformer.blocks.33.ffn.experts.mlp_experts.5.v1
- transformer.blocks.29.ffn.experts.mlp_experts.5.v1
- transformer.blocks.8.ffn.experts.mlp_experts.5.v1
- transformer.blocks.7.ffn.experts.mlp_experts.5.v1
# ffn.experts.mlp_experts.5.w1 layers
- transformer.blocks.0.ffn.experts.mlp_experts.5.w1
- transformer.blocks.6.ffn.experts.mlp_experts.5.w1
- transformer.blocks.7.ffn.experts.mlp_experts.5.w1
- transformer.blocks.9.ffn.experts.mlp_experts.5.w1
- transformer.blocks.8.ffn.experts.mlp_experts.5.w1
- transformer.blocks.12.ffn.experts.mlp_experts.5.w1
- transformer.blocks.3.ffn.experts.mlp_experts.5.w1
- transformer.blocks.5.ffn.experts.mlp_experts.5.w1
- transformer.blocks.4.ffn.experts.mlp_experts.5.w1
- transformer.blocks.33.ffn.experts.mlp_experts.5.w1
# ffn.experts.mlp_experts.5.w2 layers
- transformer.blocks.26.ffn.experts.mlp_experts.5.w2
- transformer.blocks.28.ffn.experts.mlp_experts.5.w2
- transformer.blocks.6.ffn.experts.mlp_experts.5.w2
- transformer.blocks.33.ffn.experts.mlp_experts.5.w2
- transformer.blocks.5.ffn.experts.mlp_experts.5.w2
- transformer.blocks.27.ffn.experts.mlp_experts.5.w2
- transformer.blocks.3.ffn.experts.mlp_experts.5.w2
- transformer.blocks.29.ffn.experts.mlp_experts.5.w2
- transformer.blocks.25.ffn.experts.mlp_experts.5.w2
- transformer.blocks.7.ffn.experts.mlp_experts.5.w2
# ffn.experts.mlp_experts.6.v1 layers
- transformer.blocks.34.ffn.experts.mlp_experts.6.v1
- transformer.blocks.31.ffn.experts.mlp_experts.6.v1
- transformer.blocks.30.ffn.experts.mlp_experts.6.v1
- transformer.blocks.26.ffn.experts.mlp_experts.6.v1
- transformer.blocks.35.ffn.experts.mlp_experts.6.v1
- transformer.blocks.20.ffn.experts.mlp_experts.6.v1
- transformer.blocks.15.ffn.experts.mlp_experts.6.v1
- transformer.blocks.29.ffn.experts.mlp_experts.6.v1
- transformer.blocks.10.ffn.experts.mlp_experts.6.v1
- transformer.blocks.24.ffn.experts.mlp_experts.6.v1
# ffn.experts.mlp_experts.6.w1 layers
- transformer.blocks.0.ffn.experts.mlp_experts.6.w1
- transformer.blocks.10.ffn.experts.mlp_experts.6.w1
- transformer.blocks.9.ffn.experts.mlp_experts.6.w1
- transformer.blocks.30.ffn.experts.mlp_experts.6.w1
- transformer.blocks.4.ffn.experts.mlp_experts.6.w1
- transformer.blocks.34.ffn.experts.mlp_experts.6.w1
- transformer.blocks.26.ffn.experts.mlp_experts.6.w1
- transformer.blocks.2.ffn.experts.mlp_experts.6.w1
- transformer.blocks.29.ffn.experts.mlp_experts.6.w1
- transformer.blocks.8.ffn.experts.mlp_experts.6.w1
# ffn.experts.mlp_experts.6.w2 layers
- transformer.blocks.24.ffn.experts.mlp_experts.6.w2
- transformer.blocks.26.ffn.experts.mlp_experts.6.w2
- transformer.blocks.32.ffn.experts.mlp_experts.6.w2
- transformer.blocks.30.ffn.experts.mlp_experts.6.w2
- transformer.blocks.25.ffn.experts.mlp_experts.6.w2
- transformer.blocks.31.ffn.experts.mlp_experts.6.w2
- transformer.blocks.20.ffn.experts.mlp_experts.6.w2
- transformer.blocks.4.ffn.experts.mlp_experts.6.w2
- transformer.blocks.2.ffn.experts.mlp_experts.6.w2
- transformer.blocks.9.ffn.experts.mlp_experts.6.w2
# ffn.experts.mlp_experts.7.v1 layers
- transformer.blocks.27.ffn.experts.mlp_experts.7.v1
- transformer.blocks.28.ffn.experts.mlp_experts.7.v1
- transformer.blocks.33.ffn.experts.mlp_experts.7.v1
- transformer.blocks.29.ffn.experts.mlp_experts.7.v1
- transformer.blocks.24.ffn.experts.mlp_experts.7.v1
- transformer.blocks.11.ffn.experts.mlp_experts.7.v1
- transformer.blocks.12.ffn.experts.mlp_experts.7.v1
- transformer.blocks.10.ffn.experts.mlp_experts.7.v1
- transformer.blocks.23.ffn.experts.mlp_experts.7.v1
- transformer.blocks.34.ffn.experts.mlp_experts.7.v1
# ffn.experts.mlp_experts.7.w1 layers
- transformer.blocks.12.ffn.experts.mlp_experts.7.w1
- transformer.blocks.0.ffn.experts.mlp_experts.7.w1
- transformer.blocks.5.ffn.experts.mlp_experts.7.w1
- transformer.blocks.29.ffn.experts.mlp_experts.7.w1
- transformer.blocks.10.ffn.experts.mlp_experts.7.w1
- transformer.blocks.4.ffn.experts.mlp_experts.7.w1
- transformer.blocks.3.ffn.experts.mlp_experts.7.w1
- transformer.blocks.8.ffn.experts.mlp_experts.7.w1
- transformer.blocks.34.ffn.experts.mlp_experts.7.w1
- transformer.blocks.33.ffn.experts.mlp_experts.7.w1
# ffn.experts.mlp_experts.7.w2 layers
- transformer.blocks.23.ffn.experts.mlp_experts.7.w2
- transformer.blocks.24.ffn.experts.mlp_experts.7.w2
- transformer.blocks.31.ffn.experts.mlp_experts.7.w2
- transformer.blocks.28.ffn.experts.mlp_experts.7.w2
- transformer.blocks.27.ffn.experts.mlp_experts.7.w2
- transformer.blocks.5.ffn.experts.mlp_experts.7.w2
- transformer.blocks.25.ffn.experts.mlp_experts.7.w2
- transformer.blocks.29.ffn.experts.mlp_experts.7.w2
- transformer.blocks.3.ffn.experts.mlp_experts.7.w2
- transformer.blocks.33.ffn.experts.mlp_experts.7.w2
# ffn.experts.mlp_experts.8.v1 layers
- transformer.blocks.30.ffn.experts.mlp_experts.8.v1
- transformer.blocks.27.ffn.experts.mlp_experts.8.v1
- transformer.blocks.20.ffn.experts.mlp_experts.8.v1
- transformer.blocks.32.ffn.experts.mlp_experts.8.v1
- transformer.blocks.34.ffn.experts.mlp_experts.8.v1
- transformer.blocks.33.ffn.experts.mlp_experts.8.v1
- transformer.blocks.9.ffn.experts.mlp_experts.8.v1
- transformer.blocks.7.ffn.experts.mlp_experts.8.v1
- transformer.blocks.6.ffn.experts.mlp_experts.8.v1
- transformer.blocks.24.ffn.experts.mlp_experts.8.v1
# ffn.experts.mlp_experts.8.w1 layers
- transformer.blocks.7.ffn.experts.mlp_experts.8.w1
- transformer.blocks.6.ffn.experts.mlp_experts.8.w1
- transformer.blocks.0.ffn.experts.mlp_experts.8.w1
- transformer.blocks.9.ffn.experts.mlp_experts.8.w1
- transformer.blocks.3.ffn.experts.mlp_experts.8.w1
- transformer.blocks.2.ffn.experts.mlp_experts.8.w1
- transformer.blocks.8.ffn.experts.mlp_experts.8.w1
- transformer.blocks.30.ffn.experts.mlp_experts.8.w1
- transformer.blocks.24.ffn.experts.mlp_experts.8.w1
- transformer.blocks.1.ffn.experts.mlp_experts.8.w1
# ffn.experts.mlp_experts.8.w2 layers
- transformer.blocks.32.ffn.experts.mlp_experts.8.w2
- transformer.blocks.24.ffn.experts.mlp_experts.8.w2
- transformer.blocks.27.ffn.experts.mlp_experts.8.w2
- transformer.blocks.30.ffn.experts.mlp_experts.8.w2
- transformer.blocks.31.ffn.experts.mlp_experts.8.w2
- transformer.blocks.28.ffn.experts.mlp_experts.8.w2
- transformer.blocks.2.ffn.experts.mlp_experts.8.w2
- transformer.blocks.3.ffn.experts.mlp_experts.8.w2
- transformer.blocks.23.ffn.experts.mlp_experts.8.w2
- transformer.blocks.29.ffn.experts.mlp_experts.8.w2
# ffn.experts.mlp_experts.9.v1 layers
- transformer.blocks.31.ffn.experts.mlp_experts.9.v1
- transformer.blocks.27.ffn.experts.mlp_experts.9.v1
- transformer.blocks.29.ffn.experts.mlp_experts.9.v1
- transformer.blocks.33.ffn.experts.mlp_experts.9.v1
- transformer.blocks.25.ffn.experts.mlp_experts.9.v1
- transformer.blocks.14.ffn.experts.mlp_experts.9.v1
- transformer.blocks.32.ffn.experts.mlp_experts.9.v1
- transformer.blocks.7.ffn.experts.mlp_experts.9.v1
- transformer.blocks.9.ffn.experts.mlp_experts.9.v1
- transformer.blocks.34.ffn.experts.mlp_experts.9.v1
# ffn.experts.mlp_experts.9.w1 layers
- transformer.blocks.7.ffn.experts.mlp_experts.9.w1
- transformer.blocks.1.ffn.experts.mlp_experts.9.w1
- transformer.blocks.9.ffn.experts.mlp_experts.9.w1
- transformer.blocks.2.ffn.experts.mlp_experts.9.w1
- transformer.blocks.27.ffn.experts.mlp_experts.9.w1
- transformer.blocks.12.ffn.experts.mlp_experts.9.w1
- transformer.blocks.4.ffn.experts.mlp_experts.9.w1
- transformer.blocks.6.ffn.experts.mlp_experts.9.w1
- transformer.blocks.19.ffn.experts.mlp_experts.9.w1
- transformer.blocks.8.ffn.experts.mlp_experts.9.w1
# ffn.experts.mlp_experts.9.w2 layers
- transformer.blocks.26.ffn.experts.mlp_experts.9.w2
- transformer.blocks.25.ffn.experts.mlp_experts.9.w2
- transformer.blocks.28.ffn.experts.mlp_experts.9.w2
- transformer.blocks.27.ffn.experts.mlp_experts.9.w2
- transformer.blocks.31.ffn.experts.mlp_experts.9.w2
- transformer.blocks.29.ffn.experts.mlp_experts.9.w2
- transformer.blocks.7.ffn.experts.mlp_experts.9.w2
- transformer.blocks.34.ffn.experts.mlp_experts.9.w2
- transformer.blocks.2.ffn.experts.mlp_experts.9.w2
- transformer.blocks.33.ffn.experts.mlp_experts.9.w2
# ffn.router.layer layers
- transformer.blocks.2.ffn.router.layer
- transformer.blocks.3.ffn.router.layer
- transformer.blocks.4.ffn.router.layer
- transformer.blocks.5.ffn.router.layer
- transformer.blocks.6.ffn.router.layer
- transformer.blocks.7.ffn.router.layer
- transformer.blocks.8.ffn.router.layer
- transformer.blocks.9.ffn.router.layer
- transformer.blocks.10.ffn.router.layer
- transformer.blocks.11.ffn.router.layer
# norm_attn_norm.attn.Wqkv layers
- transformer.blocks.16.norm_attn_norm.attn.Wqkv
- transformer.blocks.15.norm_attn_norm.attn.Wqkv
- transformer.blocks.11.norm_attn_norm.attn.Wqkv
- transformer.blocks.14.norm_attn_norm.attn.Wqkv
- transformer.blocks.12.norm_attn_norm.attn.Wqkv
- transformer.blocks.20.norm_attn_norm.attn.Wqkv
- transformer.blocks.10.norm_attn_norm.attn.Wqkv
- transformer.blocks.9.norm_attn_norm.attn.Wqkv
- transformer.blocks.19.norm_attn_norm.attn.Wqkv
- transformer.blocks.18.norm_attn_norm.attn.Wqkv
# norm_attn_norm.attn.out_proj layers
- transformer.blocks.1.norm_attn_norm.attn.out_proj
- transformer.blocks.18.norm_attn_norm.attn.out_proj
- transformer.blocks.2.norm_attn_norm.attn.out_proj
- transformer.blocks.16.norm_attn_norm.attn.out_proj
- transformer.blocks.0.norm_attn_norm.attn.out_proj
- transformer.blocks.39.norm_attn_norm.attn.out_proj
- transformer.blocks.23.norm_attn_norm.attn.out_proj
- transformer.blocks.8.norm_attn_norm.attn.out_proj
- transformer.blocks.24.norm_attn_norm.attn.out_proj
- transformer.blocks.19.norm_attn_norm.attn.out_proj
# norm_attn_norm.norm_1 layers
- transformer.blocks.0.norm_attn_norm.norm_1
- transformer.blocks.1.norm_attn_norm.norm_1
- transformer.blocks.2.norm_attn_norm.norm_1
- transformer.blocks.3.norm_attn_norm.norm_1
- transformer.blocks.4.norm_attn_norm.norm_1
- transformer.blocks.5.norm_attn_norm.norm_1
- transformer.blocks.6.norm_attn_norm.norm_1
- transformer.blocks.7.norm_attn_norm.norm_1
- transformer.blocks.8.norm_attn_norm.norm_1
- transformer.blocks.9.norm_attn_norm.norm_1
# norm_attn_norm.norm_2 layers
- transformer.blocks.0.norm_attn_norm.norm_2
- transformer.blocks.1.norm_attn_norm.norm_2
- transformer.blocks.2.norm_attn_norm.norm_2
- transformer.blocks.3.norm_attn_norm.norm_2
- transformer.blocks.4.norm_attn_norm.norm_2
- transformer.blocks.5.norm_attn_norm.norm_2
- transformer.blocks.6.norm_attn_norm.norm_2
- transformer.blocks.7.norm_attn_norm.norm_2
- transformer.blocks.8.norm_attn_norm.norm_2
- transformer.blocks.9.norm_attn_norm.norm_2
# transformer.norm_f layers
# transformer.wte layers
# ffn.experts.mlp_experts.11.v1 layers
- transformer.blocks.29.ffn.experts.mlp_experts.11.v1
- transformer.blocks.27.ffn.experts.mlp_experts.11.v1
- transformer.blocks.30.ffn.experts.mlp_experts.11.v1
- transformer.blocks.28.ffn.experts.mlp_experts.11.v1
- transformer.blocks.22.ffn.experts.mlp_experts.11.v1
- transformer.blocks.7.ffn.experts.mlp_experts.11.v1
- transformer.blocks.24.ffn.experts.mlp_experts.11.v1
- transformer.blocks.8.ffn.experts.mlp_experts.11.v1
- transformer.blocks.6.ffn.experts.mlp_experts.11.v1
- transformer.blocks.12.ffn.experts.mlp_experts.11.v1
dataset_prepared_path: dbrx2
val_set_size: 0.01
output_dir: ./out
sequence_len: 4096
sample_packing: true
pad_to_sequence_len: true
wandb_project: dolphin-2.9-Dbrx
wandb_watch:
wandb_run_id:
wandb_log_model:
gradient_accumulation_steps: 8
micro_batch_size: 1
num_epochs: 1
optimizer: paged_adamw_8bit
lr_scheduler: cosine
learning_rate: 1e-5
train_on_inputs: false
group_by_length: false
bf16: auto
fp16:
tf32: true
gradient_checkpointing: true
gradient_checkpointing_kwargs:
use_reentrant: false
early_stopping_patience:
# resume_from_checkpoint: /workspace/axolotl/dbrx-checkpoint
logging_steps: 1
xformers_attention:
flash_attention: true
warmup_steps: 10
evals_per_epoch: 4
eval_table_size:
saves_per_epoch: 4
save_total_limit: 2
save_steps:
debug:
deepspeed: /workspace/axolotl/deepspeed_configs/zero3_bf16_cpuoffload_params.json
weight_decay: 0.05
fsdp:
fsdp_config:
special_tokens:
bos_token: "<|endoftext|>"
eos_token: "<|im_end|>"
pad_token: "<|pad|>"
unk_token: "<|endoftext|>"
tokens:
- "<|im_start|>"
- "<|im_end|>"
out
This model was trained from scratch on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4336
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 10
- num_epochs: 1
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
0.4009 | 0.0 | 1 | 0.4328 |
0.413 | 0.25 | 587 | 0.4408 |
0.3626 | 0.5 | 1174 | 0.4368 |
0.3896 | 0.75 | 1761 | 0.4336 |
Framework versions
- Transformers 4.40.0.dev0
- Pytorch 2.2.2+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
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