---
library_name: transformers
tags:
- generated_from_trainer
model-index:
- name: myBit-Llama2-jp-127M-2B4TLike-aozora-sort-3epc
  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-aozora-sort-3epc

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: 3.2302

## 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: 100
- num_epochs: 3

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 6.9258        | 0.0883 | 100  | 5.2708          |
| 4.7937        | 0.1765 | 200  | 4.4660          |
| 4.2565        | 0.2648 | 300  | 4.1755          |
| 3.9951        | 0.3530 | 400  | 4.0060          |
| 3.8438        | 0.4413 | 500  | 3.8854          |
| 3.7223        | 0.5296 | 600  | 3.7829          |
| 3.6523        | 0.6178 | 700  | 3.7125          |
| 3.5985        | 0.7061 | 800  | 3.6535          |
| 3.5666        | 0.7944 | 900  | 3.6039          |
| 3.5519        | 0.8826 | 1000 | 3.5693          |
| 3.5365        | 0.9709 | 1100 | 3.5404          |
| 3.6085        | 1.0591 | 1200 | 3.5638          |
| 3.4953        | 1.1474 | 1300 | 3.4983          |
| 3.425         | 1.2357 | 1400 | 3.4737          |
| 3.3693        | 1.3239 | 1500 | 3.4579          |
| 3.3396        | 1.4122 | 1600 | 3.4431          |
| 3.3187        | 1.5004 | 1700 | 3.4259          |
| 3.3013        | 1.5887 | 1800 | 3.4121          |
| 3.3036        | 1.6770 | 1900 | 3.4004          |
| 3.2947        | 1.7652 | 2000 | 3.3808          |
| 3.3041        | 1.8535 | 2100 | 3.3653          |
| 3.304         | 1.9417 | 2200 | 3.3541          |
| 3.3582        | 2.0300 | 2300 | 3.4233          |
| 3.3097        | 2.1183 | 2400 | 3.3351          |
| 3.2426        | 2.2065 | 2500 | 3.3234          |
| 3.2034        | 2.2948 | 2600 | 3.3149          |
| 3.1675        | 2.3831 | 2700 | 3.3033          |
| 3.1611        | 2.4713 | 2800 | 3.2953          |
| 3.1344        | 2.5596 | 2900 | 3.2832          |
| 3.1391        | 2.6478 | 3000 | 3.2729          |
| 3.1324        | 2.7361 | 3100 | 3.2572          |
| 3.1355        | 2.8244 | 3200 | 3.2440          |
| 3.1417        | 2.9126 | 3300 | 3.2302          |


### Framework versions

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