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# bert_uncased_L-4_H-512_A-8-finetuned-eurlex

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.
It achieves the following results on the evaluation set:
- eval_loss: 0.9798
- eval_runtime: 51.2571
- eval_samples_per_second: 638.916
- eval_steps_per_second: 79.872
- epoch: 2.0
- step: 62604

## 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: 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: 3.0

### 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"], "base_model": "google/bert_uncased_L-4_H-512_A-8", "model-index": [{"name": "bert_uncased_L-4_H-512_A-8-finetuned-eurlex", "results": []}]}
transformers pytorch tensorboard safetensors bert fill-mask generated_from_trainer 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 #base_model-google/bert_uncased_L-4_H-512_A-8 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 




# bert_uncased_L-4_H-512_A-8-finetuned-eurlex

This model is a fine-tuned version of google/bert_uncased_L-4_H-512_A-8 on the None dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.9798
- eval_runtime: 51.2571
- eval_samples_per_second: 638.916
- eval_steps_per_second: 79.872
- epoch: 2.0
- step: 62604

## 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: 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: 3.0

### Framework versions

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

# bert_uncased_L-4_H-512_A-8-finetuned-eurlex

This model is a fine-tuned version of google/bert_uncased_L-4_H-512_A-8 on the None dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.9798
- eval_runtime: 51.2571
- eval_samples_per_second: 638.916
- eval_steps_per_second: 79.872
- epoch: 2.0
- step: 62604 ## 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: 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: 3.0 ### 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 #base_model-google/bert_uncased_L-4_H-512_A-8 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
 # bert_uncased_L-4_H-512_A-8-finetuned-eurlex

This model is a fine-tuned version of google/bert_uncased_L-4_H-512_A-8 on the None dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.9798
- eval_runtime: 51.2571
- eval_samples_per_second: 638.916
- eval_steps_per_second: 79.872
- epoch: 2.0
- step: 62604 ## 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: 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: 3.0 ### 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 #base_model-google/bert_uncased_L-4_H-512_A-8 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
# bert_uncased_L-4_H-512_A-8-finetuned-eurlex

This model is a fine-tuned version of google/bert_uncased_L-4_H-512_A-8 on the None dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.9798
- eval_runtime: 51.2571
- eval_samples_per_second: 638.916
- eval_steps_per_second: 79.872
- epoch: 2.0
- step: 62604## 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: 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: 3.0### Framework versions

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