|
--- |
|
license: apache-2.0 |
|
base_model: TinyLlama/TinyLlama-1.1B-Chat-v1.0 |
|
tags: |
|
- generated_from_trainer |
|
model-index: |
|
- name: tinyllama-out |
|
results: [] |
|
--- |
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl) |
|
<details><summary>See axolotl config</summary> |
|
|
|
axolotl version: `0.3.0` |
|
```yaml |
|
base_model: TinyLlama/TinyLlama-1.1B-Chat-v1.0 |
|
model_type: LlamaForCausalLM |
|
tokenizer_type: LlamaTokenizer |
|
is_llama_derived_model: true |
|
|
|
|
|
eval_sample_packing: False #Poco dato |
|
|
|
load_in_8bit: false |
|
load_in_4bit: false |
|
strict: false |
|
|
|
datasets: |
|
- path: data.json # or json |
|
ds_type: json # see other options below |
|
type: completion |
|
|
|
dataset_prepared_path: |
|
val_set_size: 0.05 |
|
# output_dir: ./lora-out |
|
|
|
sequence_len: 4096 |
|
sample_packing: true |
|
pad_to_sequence_len: true |
|
|
|
# adapter: lora |
|
# lora_model_dir: |
|
# lora_r: 32 |
|
# lora_alpha: 16 |
|
# lora_dropout: 0.05 |
|
# lora_target_linear: true |
|
# lora_fan_in_fan_out: |
|
|
|
wandb_project: |
|
wandb_entity: |
|
wandb_watch: |
|
wandb_name: |
|
wandb_log_model: |
|
output_dir: ./tinyllama-out |
|
gradient_accumulation_steps: 4 |
|
micro_batch_size: 2 |
|
num_epochs: 8 #2 |
|
optimizer: adamw_bnb_8bit |
|
lr_scheduler: cosine |
|
learning_rate: 0.0002 |
|
|
|
train_on_inputs: false |
|
group_by_length: false |
|
bf16: true |
|
fp16: false #TODO: change to true |
|
tf32: false |
|
|
|
gradient_checkpointing: true |
|
early_stopping_patience: |
|
resume_from_checkpoint: |
|
local_rank: |
|
logging_steps: 1 |
|
xformers_attention: |
|
flash_attention: true |
|
|
|
save_strategy: "no" |
|
|
|
warmup_steps: 10 |
|
evals_per_epoch: 4 |
|
# saves_per_epoch: 1 |
|
debug: |
|
deepspeed: |
|
weight_decay: 0.0 |
|
fsdp: |
|
fsdp_config: |
|
special_tokens: |
|
|
|
``` |
|
|
|
</details><br> |
|
|
|
# tinyllama-out |
|
|
|
This model is a fine-tuned version of [TinyLlama/TinyLlama-1.1B-Chat-v1.0](https://huggingface.co/TinyLlama/TinyLlama-1.1B-Chat-v1.0) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 1.8806 |
|
|
|
## 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: 0.0002 |
|
- train_batch_size: 2 |
|
- eval_batch_size: 2 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 4 |
|
- total_train_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: 8 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | |
|
|:-------------:|:-----:|:----:|:---------------:| |
|
| 1.9894 | 0.13 | 1 | 1.5790 | |
|
| 1.915 | 0.26 | 2 | 1.4849 | |
|
| 1.642 | 0.52 | 4 | 1.4032 | |
|
| 1.5396 | 0.77 | 6 | 1.4059 | |
|
| 1.3746 | 1.03 | 8 | 1.4101 | |
|
| 0.9355 | 1.23 | 10 | 1.5147 | |
|
| 0.9266 | 1.48 | 12 | 1.5291 | |
|
| 0.8006 | 1.74 | 14 | 1.4724 | |
|
| 0.7664 | 2.0 | 16 | 1.4965 | |
|
| 0.4813 | 2.16 | 18 | 1.5715 | |
|
| 0.4193 | 2.42 | 20 | 1.5436 | |
|
| 0.364 | 2.68 | 22 | 1.6040 | |
|
| 0.3592 | 2.94 | 24 | 1.5823 | |
|
| 0.1884 | 3.13 | 26 | 1.6850 | |
|
| 0.159 | 3.39 | 28 | 1.8316 | |
|
| 0.1641 | 3.65 | 30 | 1.7286 | |
|
| 0.1512 | 3.9 | 32 | 1.7029 | |
|
| 0.1563 | 4.06 | 34 | 1.7033 | |
|
| 0.0696 | 4.32 | 36 | 1.7482 | |
|
| 0.0643 | 4.58 | 38 | 1.8069 | |
|
| 0.0662 | 4.84 | 40 | 1.8410 | |
|
| 0.0709 | 5.1 | 42 | 1.8529 | |
|
| 0.0344 | 5.26 | 44 | 1.8626 | |
|
| 0.0468 | 5.52 | 46 | 1.8716 | |
|
| 0.0328 | 5.77 | 48 | 1.8761 | |
|
| 0.0353 | 6.03 | 50 | 1.8789 | |
|
| 0.0375 | 6.23 | 52 | 1.8803 | |
|
| 0.0345 | 6.48 | 54 | 1.8802 | |
|
| 0.0346 | 6.74 | 56 | 1.8806 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.37.0.dev0 |
|
- Pytorch 2.0.1 |
|
- Datasets 2.16.1 |
|
- Tokenizers 0.15.0 |
|
|
