---
library_name: transformers
license: agpl-3.0
base_model: Delta-Vector/Holland-4B-V1
tags:
- generated_from_trainer
datasets:
- NewEden/CivitAI-Prompts-Sharegpt
model-index:
- name: outputs/out2
  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/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl)
<details><summary>See axolotl config</summary>

axolotl version: `0.6.0`
```yaml
base_model: Delta-Vector/Holland-4B-V1
model_type: AutoModelForCausalLM
tokenizer_type: AutoTokenizer

trust_remote_code: true

load_in_8bit: false
load_in_4bit: false
strict: false

datasets:
  - path: NewEden/CivitAI-SD-Prompts
datasets:
  - path: NewEden/CivitAI-Prompts-Sharegpt
    type: chat_template
    chat_template: chatml
    roles_to_train: ["gpt"]
    field_messages: conversations
    message_field_role: from
    message_field_content: value
    train_on_eos: turn
    
dataset_prepared_path:
val_set_size: 0.02
output_dir: ./outputs/out2
sequence_len: 8192
sample_packing: true
eval_sample_packing: false
pad_to_sequence_len: true

plugins:
  - axolotl.integrations.liger.LigerPlugin
liger_rope: true
liger_rms_norm: true
liger_swiglu: true
liger_fused_linear_cross_entropy: true

wandb_project: SDprompter-final
wandb_entity:
wandb_watch:
wandb_name: SDprompter-final
wandb_log_model:

gradient_accumulation_steps: 16
micro_batch_size: 1
num_epochs: 4
optimizer: paged_adamw_8bit
lr_scheduler: cosine
learning_rate: 0.00001

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:
local_rank:
logging_steps: 1
xformers_attention:
flash_attention: true

warmup_ratio: 0.05
evals_per_epoch: 4
saves_per_epoch: 1
debug:
weight_decay: 0.01

special_tokens:
  pad_token: <|finetune_right_pad_id|>
  eos_token: <|eot_id|>

auto_resume_from_checkpoints: true

```

</details><br>

# outputs/out2

This model is a fine-tuned version of [Delta-Vector/Holland-4B-V1](https://huggingface.co/Delta-Vector/Holland-4B-V1) on the NewEden/CivitAI-Prompts-Sharegpt dataset.
It achieves the following results on the evaluation set:
- Loss: 3.2782

## 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
- gradient_accumulation_steps: 16
- total_train_batch_size: 16
- optimizer: Use paged_adamw_8bit with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 4
- num_epochs: 4

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 3.3357        | 0.0416 | 1    | 4.2492          |
| 2.9892        | 0.2494 | 6    | 3.6285          |
| 2.7364        | 0.4987 | 12   | 3.4675          |
| 2.7076        | 0.7481 | 18   | 3.3928          |
| 2.757         | 0.9974 | 24   | 3.3484          |
| 2.5801        | 1.2078 | 30   | 3.3286          |
| 2.6156        | 1.4571 | 36   | 3.3111          |
| 2.5308        | 1.7065 | 42   | 3.2999          |
| 2.5481        | 1.9558 | 48   | 3.2880          |
| 2.5773        | 2.1662 | 54   | 3.2840          |
| 2.5269        | 2.4156 | 60   | 3.2822          |
| 2.5418        | 2.6649 | 66   | 3.2806          |
| 2.4584        | 2.9143 | 72   | 3.2791          |
| 2.6515        | 3.1247 | 78   | 3.2789          |
| 2.4883        | 3.3740 | 84   | 3.2785          |
| 2.4193        | 3.6234 | 90   | 3.2787          |
| 2.4337        | 3.8727 | 96   | 3.2782          |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0