---
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-v0.4
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Llama-2-7b-hf-finetuned-mrpc-v0.4

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:
- Loss: 0.4018
- Accuracy: 0.8431
- F1: 0.8877

## 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: 1.6000000000000003e-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: 16

### Training results

| Training Loss | Epoch | Step | Accuracy | F1     | Validation Loss |
|:-------------:|:-----:|:----:|:--------:|:------:|:---------------:|
| No log        | 1.0   | 230  | 0.6446   | 0.7695 | 0.6542          |
| No log        | 2.0   | 460  | 0.6912   | 0.7968 | 0.5938          |
| 0.6489        | 3.0   | 690  | 0.7230   | 0.8151 | 0.5694          |
| 0.6489        | 4.0   | 920  | 0.7230   | 0.8138 | 0.5503          |
| 0.5299        | 5.0   | 1150 | 0.7402   | 0.8251 | 0.5492          |
| 0.5299        | 6.0   | 1380 | 0.7794   | 0.8432 | 0.4880          |
| 0.4687        | 7.0   | 1610 | 0.8064   | 0.8663 | 0.4559          |
| 0.4687        | 8.0   | 1840 | 0.8186   | 0.875  | 0.4298          |
| 0.374         | 9.0   | 2070 | 0.8284   | 0.8818 | 0.4210          |
| 0.374         | 10.0  | 2300 | 0.8456   | 0.8916 | 0.3953          |
| 0.3096        | 11.0  | 2530 | 0.8431   | 0.8897 | 0.4074          |
| 0.3096        | 12.0  | 2760 | 0.8407   | 0.8862 | 0.4030          |
| 0.3096        | 13.0  | 2990 | 0.3982   | 0.8456 | 0.8904          |
| 0.2799        | 14.0  | 3220 | 0.3873   | 0.8456 | 0.8881          |
| 0.2799        | 15.0  | 3450 | 0.3939   | 0.8529 | 0.8940          |
| 0.2511        | 16.0  | 3680 | 0.4018   | 0.8431 | 0.8877          |


### Framework versions

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