---
license: other
base_model: meta-llama/Meta-Llama-3-8B-Instruct
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: Interview_L3_1000rate_1e5_SFT_SFT
  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. -->

# Interview_L3_1000rate_1e5_SFT_SFT

This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0253

## 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: 1e-05
- train_batch_size: 2
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- training_steps: 1000

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.3904        | 0.0376 | 50   | 1.2452          |
| 1.1582        | 0.0752 | 100  | 0.9397          |
| 0.9079        | 0.1129 | 150  | 0.6367          |
| 0.3786        | 0.1505 | 200  | 0.4351          |
| 0.258         | 0.1881 | 250  | 0.3067          |
| 0.2163        | 0.2257 | 300  | 0.2114          |
| 0.1031        | 0.2634 | 350  | 0.1570          |
| 0.0911        | 0.3010 | 400  | 0.1205          |
| 0.0739        | 0.3386 | 450  | 0.0901          |
| 0.0503        | 0.3762 | 500  | 0.0713          |
| 0.0713        | 0.4138 | 550  | 0.0598          |
| 0.066         | 0.4515 | 600  | 0.0457          |
| 0.0181        | 0.4891 | 650  | 0.0403          |
| 0.015         | 0.5267 | 700  | 0.0358          |
| 0.0172        | 0.5643 | 750  | 0.0301          |
| 0.0314        | 0.6020 | 800  | 0.0267          |
| 0.0279        | 0.6396 | 850  | 0.0259          |
| 0.0133        | 0.6772 | 900  | 0.0254          |
| 0.0122        | 0.7148 | 950  | 0.0253          |
| 0.0126        | 0.7524 | 1000 | 0.0253          |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.0.0+cu117
- Datasets 2.19.1
- Tokenizers 0.19.1