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# bert-small-finetuned-legal-contracts-larger4010

This model is a fine-tuned version of [google/bert_uncased_L-4_H-512_A-8](https://huggingface.co/google/bert_uncased_L-4_H-512_A-8) on the None dataset.

## Model description

More information needed

## Intended uses & limitations
The model was not trained on the whole dataset which is around 9.5 GB, but only 
The first 40% of `train` + the last 10% of `train`.

```bash
datasets_train = load_dataset('albertvillanova/legal_contracts' , split='train[:40%]')
datasets_validation = load_dataset('albertvillanova/legal_contracts' , split='train[-10%:]')
```

The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 128
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1

### Framework versions

- Transformers 4.21.1
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["albertvillanova/legal_contracts"], "base_model": "google/bert_uncased_L-4_H-512_A-8", "model-index": [{"name": "bert-small-finetuned-legal-contracts-larger4010", "results": []}]}
transformers pytorch tensorboard safetensors bert fill-mask generated_from_trainer dataset:albertvillanova/legal_contracts base_model:google/bert_uncased_L-4_H-512_A-8 license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #safetensors #bert #fill-mask #generated_from_trainer #dataset-albertvillanova/legal_contracts #base_model-google/bert_uncased_L-4_H-512_A-8 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 




# bert-small-finetuned-legal-contracts-larger4010

This model is a fine-tuned version of google/bert_uncased_L-4_H-512_A-8 on the None dataset.

## Model description

More information needed

## Intended uses & limitations
The model was not trained on the whole dataset which is around 9.5 GB, but only 
The first 40% of 'train' + the last 10% of 'train'.



The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 128
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1

### Framework versions

- Transformers 4.21.1
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1

# bert-small-finetuned-legal-contracts-larger4010

This model is a fine-tuned version of google/bert_uncased_L-4_H-512_A-8 on the None dataset. ## Model description

More information needed ## Intended uses & limitations
The model was not trained on the whole dataset which is around 9.5 GB, but only 
The first 40% of 'train' + the last 10% of 'train'.



The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 128
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1 ### Framework versions

- Transformers 4.21.1
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #safetensors #bert #fill-mask #generated_from_trainer #dataset-albertvillanova/legal_contracts #base_model-google/bert_uncased_L-4_H-512_A-8 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
 # bert-small-finetuned-legal-contracts-larger4010

This model is a fine-tuned version of google/bert_uncased_L-4_H-512_A-8 on the None dataset. ## Model description

More information needed ## Intended uses & limitations
The model was not trained on the whole dataset which is around 9.5 GB, but only 
The first 40% of 'train' + the last 10% of 'train'.



The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 128
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1 ### Framework versions

- Transformers 4.21.1
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #tensorboard #safetensors #bert #fill-mask #generated_from_trainer #dataset-albertvillanova/legal_contracts #base_model-google/bert_uncased_L-4_H-512_A-8 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
# bert-small-finetuned-legal-contracts-larger4010

This model is a fine-tuned version of google/bert_uncased_L-4_H-512_A-8 on the None dataset.## Model description

More information needed## Intended uses & limitations
The model was not trained on the whole dataset which is around 9.5 GB, but only 
The first 40% of 'train' + the last 10% of 'train'.



The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 128
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1### Framework versions

- Transformers 4.21.1
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1