File size: 1,682 Bytes
b0bceb5
a0f0cb0
 
c5f29dc
 
 
 
 
b0bceb5
 
c5f29dc
 
b0bceb5
c5f29dc
b0bceb5
a0f0cb0
c5f29dc
a0f0cb0
b0bceb5
c5f29dc
b0bceb5
c5f29dc
b0bceb5
c5f29dc
b0bceb5
c5f29dc
b0bceb5
c5f29dc
b0bceb5
c5f29dc
b0bceb5
c5f29dc
b0bceb5
c5f29dc
b0bceb5
c5f29dc
a0f0cb0
 
c5f29dc
 
 
 
a0f0cb0
 
b0bceb5
c5f29dc
b0bceb5
a0f0cb0
 
 
 
 
 
 
 
 
b0bceb5
 
c5f29dc
b0bceb5
a0f0cb0
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
---
license: cc
base_model: joelniklaus/legal-xlm-roberta-base
tags:
- generated_from_trainer
model-index:
- name: bert-leg-al-corpus
  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. -->

# bert-leg-al-corpus

This model is a fine-tuned version of [joelniklaus/legal-xlm-roberta-base](https://huggingface.co/joelniklaus/legal-xlm-roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8639

## 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-06
- train_batch_size: 24
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 2.408         | 0.6329 | 100  | 2.0952          |
| 2.1264        | 1.2658 | 200  | 1.9866          |
| 2.0701        | 1.8987 | 300  | 1.9136          |
| 2.0156        | 2.5316 | 400  | 1.8920          |
| 2.004         | 3.1646 | 500  | 1.8745          |
| 1.9702        | 3.7975 | 600  | 1.8537          |
| 1.9569        | 4.4304 | 700  | 1.8493          |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1