---
base_model: meta-llama/Meta-Llama-3.1-70B
library_name: peft
license: llama3.1
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: english_tm_model
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# english_tm_model

This model is a fine-tuned version of [meta-llama/Meta-Llama-3.1-70B](https://huggingface.co./meta-llama/Meta-Llama-3.1-70B) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2883

## 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: 0.0002
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 8
- 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: 25
- training_steps: 300
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.75          | 0.32  | 50   | 1.3528          |
| 1.338         | 0.64  | 100  | 1.3195          |
| 1.3357        | 0.96  | 150  | 1.2975          |
| 1.2553        | 1.28  | 200  | 1.2956          |
| 1.2688        | 1.6   | 250  | 1.2909          |
| 1.2363        | 1.92  | 300  | 1.2883          |


### Framework versions

- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.1.0+cu118
- Datasets 2.21.0
- Tokenizers 0.19.1