---
library_name: transformers
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: legalcase_outcomepred_model
  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. -->

# legalcase_outcomepred_model

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0116
- Accuracy: 0.3307

## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 1.7752        | 0.9981 | 132  | 1.8412          | 0.2640   |
| 1.6453        | 1.9962 | 264  | 1.8323          | 0.2867   |
| 1.6322        | 2.9943 | 396  | 1.7919          | 0.2985   |
| 1.4239        | 4.0    | 529  | 1.8052          | 0.3188   |
| 1.3082        | 4.9981 | 661  | 1.8625          | 0.3217   |
| 1.2395        | 5.9962 | 793  | 1.8780          | 0.3382   |
| 1.103         | 6.9943 | 925  | 1.9332          | 0.3302   |
| 1.0687        | 8.0    | 1058 | 1.9723          | 0.3382   |
| 1.0303        | 8.9981 | 1190 | 2.0012          | 0.3363   |
| 0.9643        | 9.9811 | 1320 | 2.0116          | 0.3307   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.0
- Datasets 3.0.0
- Tokenizers 0.19.1