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# minilm-imdb

This model is a fine-tuned version of [microsoft/MiniLM-L12-H384-uncased](https://huggingface.co/microsoft/MiniLM-L12-H384-uncased) on imdb dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2403
- Accuracy: 0.9229
- F1: 0.9228

## 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: 4
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.1511        | 1.0   | 293  | 0.2212          | 0.9234   | 0.9229 |
| 0.1047        | 2.0   | 586  | 0.2211          | 0.9230   | 0.9217 |
| 0.1008        | 3.0   | 879  | 0.2403          | 0.9229   | 0.9228 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.0
- Tokenizers 0.15.0
{"language": ["en"], "license": "mit", "tags": ["generated_from_trainer"], "datasets": ["imdb"], "metrics": ["accuracy", "f1"], "base_model": "microsoft/MiniLM-L12-H384-uncased", "pipeline_tag": "text-classification", "model-index": [{"name": "minilm-imdb", "results": [{"task": {"type": "text-classification", "name": "text-classification"}, "dataset": {"name": "imdb", "type": "imdb", "config": "default", "split": "train", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.92288, "name": "accuracy"}, {"type": "f1", "value": 0.922831, "name": "f1"}]}]}]}
transformers tensorboard safetensors bert text-classification generated_from_trainer en dataset:imdb base_model:microsoft/MiniLM-L12-H384-uncased license:mit model-index autotrain_compatible endpoints_compatible region:us