---
license: other
library_name: peft
tags:
- generated_from_trainer
base_model: Qwen/Qwen1.5-7B
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 [Qwen/Qwen1.5-7B](https://huggingface.co/Qwen/Qwen1.5-7B) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6125
- Accuracy: 0.5507
- F1 Macro: 0.4051
- F1 Micro: 0.5507

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:--------:|
| 2.3973        | 0.32  | 50   | 2.1948          | 0.38     | 0.1677   | 0.38     |
| 1.6438        | 0.64  | 100  | 1.8118          | 0.4271   | 0.2466   | 0.4271   |
| 1.7379        | 0.96  | 150  | 1.7119          | 0.4771   | 0.2704   | 0.4771   |
| 1.409         | 1.27  | 200  | 1.7488          | 0.4871   | 0.2973   | 0.4871   |
| 1.2443        | 1.59  | 250  | 1.6798          | 0.5364   | 0.3334   | 0.5364   |
| 1.1602        | 1.91  | 300  | 1.6132          | 0.5243   | 0.3573   | 0.5243   |
| 1.1191        | 2.23  | 350  | 1.6507          | 0.5386   | 0.3914   | 0.5386   |
| 0.8907        | 2.55  | 400  | 1.6125          | 0.5507   | 0.4051   | 0.5507   |
| 0.9012        | 2.87  | 450  | 1.6445          | 0.5529   | 0.4088   | 0.5529   |


### Framework versions

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