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---
license: cc-by-sa-4.0
tags:
- generated_from_trainer
datasets:
- lex_glue
model-index:
- name: ECHR_test_2
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. -->
# ECHR_test_2
This model is a fine-tuned version of [nlpaueb/legal-bert-base-uncased](https://huggingface.co/nlpaueb/legal-bert-base-uncased) on the lex_glue dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2263
- Macro-f1: 0.3868
- Micro-f1: 0.5469
## 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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Macro-f1 | Micro-f1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|
| 0.2058 | 0.44 | 500 | 0.2743 | 0.3073 | 0.4578 |
| 0.1583 | 0.89 | 1000 | 0.2576 | 0.3335 | 0.5014 |
| 0.1602 | 1.33 | 1500 | 0.2343 | 0.3632 | 0.5341 |
| 0.1474 | 1.78 | 2000 | 0.2263 | 0.3868 | 0.5469 |
### Framework versions
- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1
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