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# testing1

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the massive dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7285
- Accuracy: 0.8928

## 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: 16
- eval_batch_size: 16
- seed: 33
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4751        | 1.0   | 720  | 0.6154          | 0.8593   |
| 0.4363        | 2.0   | 1440 | 0.4945          | 0.8800   |
| 0.2325        | 3.0   | 2160 | 0.5608          | 0.8834   |
| 0.1349        | 4.0   | 2880 | 0.6023          | 0.8800   |
| 0.0887        | 5.0   | 3600 | 0.6301          | 0.8869   |
| 0.0575        | 6.0   | 4320 | 0.6649          | 0.8898   |
| 0.0358        | 7.0   | 5040 | 0.7023          | 0.8908   |
| 0.0218        | 8.0   | 5760 | 0.7419          | 0.8913   |
| 0.0184        | 9.0   | 6480 | 0.7285          | 0.8928   |
| 0.0126        | 10.0  | 7200 | 0.7207          | 0.8908   |
| 0.0072        | 11.0  | 7920 | 0.7453          | 0.8923   |
| 0.0056        | 12.0  | 8640 | 0.7746          | 0.8918   |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.0.1+cu117
- Datasets 2.15.0
- Tokenizers 0.15.0

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["massive"], "metrics": ["accuracy"], "base_model": "bert-base-uncased", "model-index": [{"name": "testing1", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "massive", "type": "massive", "config": "en-US", "split": "validation", "args": "en-US"}, "metrics": [{"type": "accuracy", "value": 0.8927693064436792, "name": "Accuracy"}]}]}]}
transformers tensorboard safetensors bert text-classification generated_from_trainer dataset:massive base_model:bert-base-uncased license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us