---
license: other
library_name: peft
tags:
- generated_from_trainer
base_model: google/gemma-7b
metrics:
- accuracy
model-index:
- name: lex_glue
  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. -->

# lex_glue

This model is a fine-tuned version of [google/gemma-7b](https://huggingface.co/google/gemma-7b) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7927
- Accuracy: 0.4607
- F1 Macro: 0.2464
- F1 Micro: 0.4607

## 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
- distributed_type: multi-GPU
- num_devices: 2
- total_train_batch_size: 32
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | F1 Micro |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:--------:|
| 2.525         | 0.32  | 50   | 2.5147          | 0.1571   | 0.0284   | 0.1571   |
| 2.1941        | 0.64  | 100  | 2.2338          | 0.28     | 0.0652   | 0.28     |
| 2.1844        | 0.96  | 150  | 2.0491          | 0.3507   | 0.0976   | 0.3507   |
| 2.0301        | 1.27  | 200  | 2.1722          | 0.2836   | 0.1127   | 0.2836   |
| 1.7887        | 1.59  | 250  | 2.0104          | 0.415    | 0.1541   | 0.415    |
| 1.7363        | 1.91  | 300  | 1.8959          | 0.4079   | 0.1816   | 0.4079   |
| 1.5688        | 2.23  | 350  | 1.8491          | 0.4121   | 0.2279   | 0.4121   |
| 1.4951        | 2.55  | 400  | 1.8011          | 0.4564   | 0.2391   | 0.4564   |
| 1.3732        | 2.87  | 450  | 1.7927          | 0.4607   | 0.2464   | 0.4607   |


### Framework versions

- PEFT 0.9.0
- Transformers 4.39.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2