---
library_name: transformers
tags:
- generated_from_trainer
model-index:
- name: cllm-0.0.2
  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. -->

# cllm-0.0.2

This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.5767

## 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: 0.0003
- train_batch_size: 8
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- total_eval_batch_size: 32
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- num_epochs: 1

### Training results

| Training Loss | Epoch  | Step  | Validation Loss |
|:-------------:|:------:|:-----:|:---------------:|
| 4.8419        | 0.0214 | 500   | 4.7291          |
| 3.891         | 0.0429 | 1000  | 3.8792          |
| 3.5798        | 0.0643 | 1500  | 3.5656          |
| 3.3861        | 0.0858 | 2000  | 3.4057          |
| 3.2754        | 0.1072 | 2500  | 3.2925          |
| 3.2039        | 0.1286 | 3000  | 3.2109          |
| 3.1475        | 0.1501 | 3500  | 3.1513          |
| 3.0936        | 0.1715 | 4000  | 3.0991          |
| 3.0483        | 0.1930 | 4500  | 3.0603          |
| 3.0036        | 0.2144 | 5000  | 3.0180          |
| 2.9644        | 0.2358 | 5500  | 2.9900          |
| 2.9374        | 0.2573 | 6000  | 2.9599          |
| 2.901         | 0.2787 | 6500  | 2.9334          |
| 2.8968        | 0.3002 | 7000  | 2.9124          |
| 2.866         | 0.3216 | 7500  | 2.8889          |
| 2.8614        | 0.3430 | 8000  | 2.8672          |
| 2.8378        | 0.3645 | 8500  | 2.8489          |
| 2.8242        | 0.3859 | 9000  | 2.8290          |
| 2.7961        | 0.4074 | 9500  | 2.8133          |
| 2.769         | 0.4288 | 10000 | 2.7962          |
| 2.7619        | 0.4502 | 10500 | 2.7804          |
| 2.7527        | 0.4717 | 11000 | 2.7687          |
| 2.7457        | 0.4931 | 11500 | 2.7540          |
| 2.7119        | 0.5146 | 12000 | 2.7441          |
| 2.7089        | 0.5360 | 12500 | 2.7317          |
| 2.7236        | 0.5574 | 13000 | 2.7218          |
| 2.6984        | 0.5789 | 13500 | 2.7102          |
| 2.6791        | 0.6003 | 14000 | 2.6998          |
| 2.6764        | 0.6218 | 14500 | 2.6915          |
| 2.6663        | 0.6432 | 15000 | 2.6806          |
| 2.6424        | 0.6646 | 15500 | 2.6720          |
| 2.6384        | 0.6861 | 16000 | 2.6612          |
| 2.6343        | 0.7075 | 16500 | 2.6536          |
| 2.6303        | 0.7290 | 17000 | 2.6471          |
| 2.6115        | 0.7504 | 17500 | 2.6373          |
| 2.6125        | 0.7718 | 18000 | 2.6310          |
| 2.5983        | 0.7933 | 18500 | 2.6246          |
| 2.6043        | 0.8147 | 19000 | 2.6173          |
| 2.5876        | 0.8362 | 19500 | 2.6106          |
| 2.5824        | 0.8576 | 20000 | 2.6043          |
| 2.5802        | 0.8790 | 20500 | 2.5983          |
| 2.5772        | 0.9005 | 21000 | 2.5927          |
| 2.5584        | 0.9219 | 21500 | 2.5878          |
| 2.5652        | 0.9434 | 22000 | 2.5835          |
| 2.5593        | 0.9648 | 22500 | 2.5794          |
| 2.5547        | 0.9862 | 23000 | 2.5767          |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.1.0+cu118
- Datasets 3.2.0
- Tokenizers 0.21.0