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---
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: legalbert-large-1.7M-2_class_actions
  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. -->

# legalbert-large-1.7M-2_class_actions

This model is a fine-tuned version of [pile-of-law/legalbert-large-1.7M-2](https://huggingface.co/pile-of-law/legalbert-large-1.7M-2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6428
- Accuracy: 0.61

## 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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 14

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 150  | 0.6380          | 0.6333   |
| No log        | 2.0   | 300  | 0.7457          | 0.55     |
| No log        | 3.0   | 450  | 0.7066          | 0.45     |
| 0.6843        | 4.0   | 600  | 0.7218          | 0.6767   |
| 0.6843        | 5.0   | 750  | 0.6360          | 0.6067   |
| 0.6843        | 6.0   | 900  | 0.6502          | 0.6033   |
| 0.6751        | 7.0   | 1050 | 0.6664          | 0.6033   |
| 0.6751        | 8.0   | 1200 | 0.6490          | 0.6133   |
| 0.6751        | 9.0   | 1350 | 0.6506          | 0.6067   |
| 0.6781        | 10.0  | 1500 | 0.6486          | 0.61     |
| 0.6781        | 11.0  | 1650 | 0.6544          | 0.6167   |
| 0.6781        | 12.0  | 1800 | 0.6425          | 0.61     |
| 0.6781        | 13.0  | 1950 | 0.6417          | 0.61     |
| 0.6756        | 14.0  | 2100 | 0.6428          | 0.61     |


### Framework versions

- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3