---
license: llama3
base_model: meta-llama/Meta-Llama-3-8B-Instruct
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: UTI_L3_1000steps_1e7rate_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. -->

# UTI_L3_1000steps_1e7rate_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: 1.6055

## 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-07
- 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 |
|:-------------:|:-------:|:----:|:---------------:|
| 2.4485        | 0.3333  | 25   | 2.4666          |
| 2.4645        | 0.6667  | 50   | 2.4522          |
| 2.452         | 1.0     | 75   | 2.4164          |
| 2.391         | 1.3333  | 100  | 2.3529          |
| 2.2816        | 1.6667  | 125  | 2.2866          |
| 2.175         | 2.0     | 150  | 2.2255          |
| 2.2168        | 2.3333  | 175  | 2.1683          |
| 2.1574        | 2.6667  | 200  | 2.1166          |
| 2.1107        | 3.0     | 225  | 2.0679          |
| 2.0126        | 3.3333  | 250  | 2.0229          |
| 1.9353        | 3.6667  | 275  | 1.9810          |
| 1.9552        | 4.0     | 300  | 1.9445          |
| 1.9759        | 4.3333  | 325  | 1.9100          |
| 1.8721        | 4.6667  | 350  | 1.8773          |
| 1.8928        | 5.0     | 375  | 1.8491          |
| 1.8331        | 5.3333  | 400  | 1.8236          |
| 1.8221        | 5.6667  | 425  | 1.7980          |
| 1.7615        | 6.0     | 450  | 1.7762          |
| 1.7701        | 6.3333  | 475  | 1.7562          |
| 1.7034        | 6.6667  | 500  | 1.7327          |
| 1.7471        | 7.0     | 525  | 1.7064          |
| 1.7317        | 7.3333  | 550  | 1.6831          |
| 1.6897        | 7.6667  | 575  | 1.6645          |
| 1.6452        | 8.0     | 600  | 1.6476          |
| 1.6675        | 8.3333  | 625  | 1.6327          |
| 1.569         | 8.6667  | 650  | 1.6238          |
| 1.705         | 9.0     | 675  | 1.6163          |
| 1.6025        | 9.3333  | 700  | 1.6121          |
| 1.6224        | 9.6667  | 725  | 1.6083          |
| 1.6976        | 10.0    | 750  | 1.6074          |
| 1.6031        | 10.3333 | 775  | 1.6059          |
| 1.5703        | 10.6667 | 800  | 1.6046          |
| 1.6563        | 11.0    | 825  | 1.6055          |
| 1.6464        | 11.3333 | 850  | 1.6059          |
| 1.6075        | 11.6667 | 875  | 1.6055          |
| 1.6453        | 12.0    | 900  | 1.6057          |
| 1.5754        | 12.3333 | 925  | 1.6054          |
| 1.5962        | 12.6667 | 950  | 1.6055          |
| 1.6333        | 13.0    | 975  | 1.6055          |
| 1.6086        | 13.3333 | 1000 | 1.6055          |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.0.0+cu117
- Datasets 2.19.2
- Tokenizers 0.19.1