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

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: 2.8431

## 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: 12
- eval_batch_size: 12
- seed: 42
- gradient_accumulation_steps: 8
- 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 |
|:-------------:|:------:|:----:|:---------------:|
| 4.9846        | 0.0587 | 500  | 5.1982          |
| 3.7747        | 0.1175 | 1000 | 4.4941          |
| 3.5109        | 0.1762 | 1500 | 4.0737          |
| 3.3568        | 0.2350 | 2000 | 3.8909          |
| 3.276         | 0.2937 | 2500 | 3.7147          |
| 3.2203        | 0.3525 | 3000 | 3.5468          |
| 3.1626        | 0.4112 | 3500 | 3.4098          |
| 3.1272        | 0.4700 | 4000 | 3.3188          |
| 3.0925        | 0.5287 | 4500 | 3.2339          |
| 3.0693        | 0.5874 | 5000 | 3.1539          |
| 3.0412        | 0.6462 | 5500 | 3.0721          |
| 2.9981        | 0.7049 | 6000 | 3.0009          |
| 2.9881        | 0.7637 | 6500 | 2.9514          |
| 2.9871        | 0.8224 | 7000 | 2.9162          |
| 2.9796        | 0.8812 | 7500 | 2.8879          |
| 2.9914        | 0.9399 | 8000 | 2.8849          |
| 2.9649        | 0.9987 | 8500 | 2.8431          |


### Framework versions

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