---
license: mit
base_model: croissantllm/CroissantCool-v0.2
tags:
- generated_from_trainer
model-index:
- name: gpfs/workdir/fayssema/models/out_newtok_dataset1
  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: `0.4.0`
```yaml
base_model: croissantllm/CroissantCool-v0.2                                                                                                                                                                   
model_type: LlamaForCausalLM                                                                                                                                                                                
tokenizer_type: LlamaTokenizerFast                                                                                                                                                                              
is_llama_derived_model: true                                                                                                                                                                                

special_tokens:
  bos_token: "<s>"
  eos_token: "</s>"
  unk_token: "<unk>"

tokens:
  - "<|im_start|>"
  - "<|im_end|>"
                                                                                                                                                                                                            
load_in_8bit: false                                                                                                                                                                                         
load_in_4bit: false                                                                                                                                                                                         
strict: false                                                                                                                                                                                               
                                                                                                                                                                                                            
datasets:                                                                                                                                                                                                   
  - path: manu/dataset_1
    split: train                                                                                                                                                              
    type: sharegpt

chat_template: "chatml"
default_system_message: null

dataset_prepared_path: new_pii_2 
val_set_size: 0.05                       
output_dir: /gpfs/workdir/fayssema/models/out_newtok_dataset1
                                                                                                                                                                                                            
sequence_len: 2048                                                                                                                                                                                          
sample_packing: false                                                                                                                                                                                       
pad_to_sequence_len: false                                                                                                                                                                                   
                                                                                                                                                                                                            
adapter:                                                                                                                                                                                                    
lora_model_dir:                                                                                                                                                                                             
lora_r:                                                                                                                                                                                                     
lora_alpha:                                                                                                                                                                                                 
lora_dropout:
lora_target_linear:
lora_fan_in_fan_out:

wandb_project:
wandb_entity:
wandb_watch:
wandb_name:
wandb_log_model:

gradient_accumulation_steps: 2
micro_batch_size: 16
num_epochs: 3
# optimizer: adamw_bnb_8bit
lr_scheduler: cosine
learning_rate: 0.00003

train_on_inputs: false
group_by_length: false
bf16: auto
fp16: false
tf32: true

gradient_checkpointing: true
early_stopping_patience:
resume_from_checkpoint:
local_rank:
logging_steps: 1
xformers_attention:
flash_attention: true
flash_attn_cross_entropy: false
flash_attn_rms_norm: true
flash_attn_fuse_qkv: false
flash_attn_fuse_mlp: true

warmup_steps: 100
evals_per_epoch: 4
eval_table_size:
saves_per_epoch: 1
debug:
deepspeed: #deepspeed_configs/zero2.json # multi-gpu only
weight_decay: 0.05
fsdp:
fsdp_config:

```

</details><br>

# gpfs/workdir/fayssema/models/out_newtok_dataset1

This model is a fine-tuned version of [croissantllm/CroissantCool-v0.2](https://huggingface.co/croissantllm/CroissantCool-v0.2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0087

## 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: 3e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.0845        | 0.0   | 1    | 0.8684          |
| 0.1841        | 0.25  | 73   | 0.0205          |
| 0.2394        | 0.51  | 146  | 0.0134          |
| 0.1685        | 0.76  | 219  | 0.0128          |
| 0.1385        | 1.01  | 292  | 0.0209          |
| 0.1561        | 1.26  | 365  | 0.0128          |
| 0.1352        | 1.52  | 438  | 0.0090          |
| 0.162         | 1.77  | 511  | 0.0094          |
| 0.0661        | 2.02  | 584  | 0.0085          |
| 0.1344        | 2.27  | 657  | 0.0089          |
| 0.0718        | 2.53  | 730  | 0.0088          |
| 0.0942        | 2.78  | 803  | 0.0087          |


### Framework versions

- Transformers 4.38.0.dev0
- Pytorch 2.3.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0