tensorboard generated_from_trainer dataset:glue base_model:meta-llama/Llama-2-7b-hf region:us
---
base_model: meta-llama/Llama-2-7b-hf
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: Llama-2-7b-hf-finetuned-mrpc
  results: []
---

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# Llama-2-7b-hf-finetuned-mrpc

This model is a fine-tuned version of [meta-llama/Llama-2-7b-hf](https://huggingface.co/meta-llama/Llama-2-7b-hf) on the glue dataset.
It achieves the following results on the evaluation set:
- Accuracy: 0.7941
- F1: 0.8571
- Loss: 0.4479

## 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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Accuracy | F1     | Validation Loss |
|:-------------:|:-----:|:----:|:--------:|:------:|:---------------:|
| No log        | 1.0   | 230  | 0.7206   | 0.8155 | 0.6045          |
| No log        | 2.0   | 460  | 0.6912   | 0.8158 | 0.6488          |
| 0.6326        | 3.0   | 690  | 0.7279   | 0.8235 | 0.5236          |
| 0.6326        | 4.0   | 920  | 0.7255   | 0.8282 | 0.5273          |
| 0.5602        | 5.0   | 1150 | 0.7402   | 0.8044 | 0.5246          |
| 0.5602        | 6.0   | 1380 | 0.75     | 0.8311 | 0.4893          |
| 0.5139        | 7.0   | 1610 | 0.7623   | 0.8289 | 0.4884          |
| 0.5139        | 8.0   | 1840 | 0.7402   | 0.8307 | 0.4989          |
| 0.4754        | 9.0   | 2070 | 0.7745   | 0.8435 | 0.4732          |
| 0.4754        | 10.0  | 2300 | 0.7672   | 0.8403 | 0.4716          |
| 0.5407        | 11.0  | 2530 | 0.7598   | 0.8393 | 0.4823          |
| 0.5407        | 12.0  | 2760 | 0.7451   | 0.8333 | 0.4782          |
| 0.5407        | 13.0  | 2990 | 0.7451   | 0.8333 | 0.4713          |
| 0.4951        | 14.0  | 3220 | 0.7819   | 0.8489 | 0.4553          |
| 0.4951        | 15.0  | 3450 | 0.7745   | 0.8506 | 0.4591          |
| 0.4724        | 16.0  | 3680 | 0.7770   | 0.8423 | 0.4631          |
| 0.4724        | 17.0  | 3910 | 0.8015   | 0.8576 | 0.4581          |
| 0.4455        | 18.0  | 4140 | 0.7819   | 0.8468 | 0.4548          |
| 0.4455        | 19.0  | 4370 | 0.7819   | 0.8484 | 0.4511          |
| 0.4354        | 20.0  | 4600 | 0.7941   | 0.8571 | 0.4479          |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
