---
library_name: transformers
tags:
- generated_from_trainer
model-index:
- name: myBit-Llama2-jp-127M-2B4TLike-wiki-aozora-sort-swallow-tokenizer
  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. -->

# myBit-Llama2-jp-127M-2B4TLike-wiki-aozora-sort-swallow-tokenizer

This model is a fine-tuned version of [](https://huggingface.co/) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 3.0804

## 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: 0.0024
- train_batch_size: 24
- eval_batch_size: 24
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 96
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.95) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 750
- num_epochs: 1

### Training results

| Training Loss | Epoch  | Step  | Validation Loss |
|:-------------:|:------:|:-----:|:---------------:|
| 5.0217        | 0.0437 | 500   | 5.5967          |
| 3.8655        | 0.0875 | 1000  | 4.9636          |
| 3.5798        | 0.1312 | 1500  | 4.5889          |
| 3.4331        | 0.1749 | 2000  | 4.3685          |
| 3.3371        | 0.2187 | 2500  | 4.2415          |
| 3.2912        | 0.2624 | 3000  | 4.1319          |
| 3.2255        | 0.3061 | 3500  | 4.0167          |
| 3.1863        | 0.3499 | 4000  | 3.9057          |
| 3.1549        | 0.3936 | 4500  | 3.7257          |
| 3.1237        | 0.4373 | 5000  | 3.6422          |
| 3.1066        | 0.4811 | 5500  | 3.5338          |
| 3.0786        | 0.5248 | 6000  | 3.4784          |
| 3.051         | 0.5686 | 6500  | 3.4182          |
| 3.0279        | 0.6123 | 7000  | 3.3684          |
| 3.0516        | 0.6560 | 7500  | 3.3032          |
| 3.1796        | 0.6998 | 8000  | 3.2376          |
| 3.1997        | 0.7435 | 8500  | 3.2020          |
| 3.172         | 0.7872 | 9000  | 3.1750          |
| 3.1487        | 0.8310 | 9500  | 3.1502          |
| 3.1296        | 0.8747 | 10000 | 3.1273          |
| 3.0886        | 0.9184 | 10500 | 3.1030          |
| 3.0402        | 0.9622 | 11000 | 3.0804          |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.6.0+cu124
- Datasets 3.5.1
- Tokenizers 0.21.1