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# legal_long_legal_ver2_test_sm

This model is a fine-tuned version of [kiddothe2b/legal-longformer-base](https://huggingface.co/kiddothe2b/legal-longformer-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.7379
- Accuracy: 0.5519
- Precision: 0.5139
- Recall: 0.5663
- F1: 0.5388
- D-index: 1.2690

## 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: 8
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     | D-index |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:-------:|
| No log        | 0.98  | 26   | 0.6957          | 0.4599   | 0.44      | 0.6173 | 0.5138 | 1.1026  |
| No log        | 2.0   | 53   | 0.6960          | 0.4528   | 0.4262    | 0.5306 | 0.4727 | 1.0831  |
| No log        | 2.98  | 79   | 0.6978          | 0.4481   | 0.4312    | 0.6071 | 0.5042 | 1.0794  |
| No log        | 4.0   | 106  | 0.7232          | 0.4788   | 0.4622    | 0.7806 | 0.5806 | 1.1493  |
| No log        | 4.98  | 132  | 0.7340          | 0.5189   | 0.4828    | 0.5714 | 0.5234 | 1.2095  |
| No log        | 6.0   | 159  | 0.8623          | 0.5425   | 0.5049    | 0.5255 | 0.515  | 1.2493  |
| No log        | 6.98  | 185  | 1.2325          | 0.5448   | 0.5116    | 0.3367 | 0.4062 | 1.2412  |
| No log        | 8.0   | 212  | 1.4773          | 0.5165   | 0.4717    | 0.3827 | 0.4225 | 1.1925  |
| No log        | 8.98  | 238  | 1.6199          | 0.5330   | 0.4941    | 0.4286 | 0.4590 | 1.2258  |
| No log        | 10.0  | 265  | 1.8976          | 0.5259   | 0.4900    | 0.6276 | 0.5503 | 1.2261  |
| No log        | 10.98 | 291  | 2.1687          | 0.4953   | 0.4622    | 0.5612 | 0.5069 | 1.1653  |
| No log        | 12.0  | 318  | 2.3087          | 0.4882   | 0.4578    | 0.5816 | 0.5124 | 1.1535  |
| No log        | 12.98 | 344  | 2.5168          | 0.4953   | 0.4667    | 0.6429 | 0.5408 | 1.1708  |
| No log        | 14.0  | 371  | 2.5389          | 0.5142   | 0.4788    | 0.5765 | 0.5231 | 1.2012  |
| No log        | 14.98 | 397  | 2.4224          | 0.5330   | 0.4957    | 0.5918 | 0.5395 | 1.2366  |
| No log        | 16.0  | 424  | 2.6391          | 0.5212   | 0.4852    | 0.5867 | 0.5312 | 1.2148  |
| No log        | 16.98 | 450  | 2.7235          | 0.5307   | 0.4932    | 0.5510 | 0.5205 | 1.2297  |
| No log        | 18.0  | 477  | 2.7272          | 0.5425   | 0.5045    | 0.5765 | 0.5381 | 1.2527  |
| 0.2333        | 18.98 | 503  | 2.7222          | 0.5495   | 0.5117    | 0.5561 | 0.5330 | 1.2641  |
| 0.2333        | 19.62 | 520  | 2.7379          | 0.5519   | 0.5139    | 0.5663 | 0.5388 | 1.2690  |


### Framework versions

- Transformers 4.27.4
- Pytorch 1.13.1+cu116
- Datasets 2.11.0
- Tokenizers 0.13.2

{"license": "cc-by-nc-sa-4.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy", "precision", "recall", "f1"], "model-index": [{"name": "legal_long_legal_ver2_test_sm", "results": []}]}
transformers pytorch tensorboard longformer text-classification generated_from_trainer license:cc-by-nc-sa-4.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #longformer #text-classification #generated_from_trainer #license-cc-by-nc-sa-4.0 #autotrain_compatible #endpoints_compatible #region-us 

legal\_long\_legal\_ver2\_test\_sm
==================================


This model is a fine-tuned version of kiddothe2b/legal-longformer-base on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 2.7379
* Accuracy: 0.5519
* Precision: 0.5139
* Recall: 0.5663
* F1: 0.5388
* D-index: 1.2690


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: 8
* eval\_batch\_size: 16
* seed: 42
* gradient\_accumulation\_steps: 8
* total\_train\_batch\_size: 64
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 200
* num\_epochs: 20


### Training results



### Framework versions


* Transformers 4.27.4
* Pytorch 1.13.1+cu116
* Datasets 2.11.0
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 8
* eval\_batch\_size: 16
* seed: 42
* gradient\_accumulation\_steps: 8
* total\_train\_batch\_size: 64
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 200
* num\_epochs: 20 ### Training results ### Framework versions


* Transformers 4.27.4
* Pytorch 1.13.1+cu116
* Datasets 2.11.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #longformer #text-classification #generated_from_trainer #license-cc-by-nc-sa-4.0 #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 8
* eval\_batch\_size: 16
* seed: 42
* gradient\_accumulation\_steps: 8
* total\_train\_batch\_size: 64
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 200
* num\_epochs: 20 ### Training results ### Framework versions


* Transformers 4.27.4
* Pytorch 1.13.1+cu116
* Datasets 2.11.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #longformer #text-classification #generated_from_trainer #license-cc-by-nc-sa-4.0 #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 8
* eval\_batch\_size: 16
* seed: 42
* gradient\_accumulation\_steps: 8
* total\_train\_batch\_size: 64
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 200
* num\_epochs: 20### Training results### Framework versions


* Transformers 4.27.4
* Pytorch 1.13.1+cu116
* Datasets 2.11.0
* Tokenizers 0.13.2