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# roberta-large-flash-attention-2-lora-patent-classification

This model is a fine-tuned version of [roberta-large](https://huggingface.co/roberta-large) on the patent-classification dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8395
- Accuracy: 0.6304
- Precision Macro: 0.6136
- Recall Macro: 0.5995
- F1-score Macro: 0.5984

## 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: 6
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | Precision Macro | Recall Macro | F1-score Macro |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------------:|:------------:|:--------------:|
| 0.7566        | 1.0   | 4167  | 0.9131          | 0.5692   | 0.6231          | 0.5423       | 0.5631         |
| 0.6974        | 2.0   | 8334  | 0.8428          | 0.6174   | 0.6169          | 0.5910       | 0.5942         |
| 0.7219        | 3.0   | 12501 | 0.8395          | 0.6304   | 0.6136          | 0.5995       | 0.5984         |


### Framework versions

- PEFT 0.7.2.dev0
- Transformers 4.37.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.16.2.dev0
- Tokenizers 0.15.0
{"license": "mit", "library_name": "peft", "tags": ["generated_from_trainer"], "datasets": ["patent-classification"], "metrics": ["accuracy"], "base_model": "roberta-large", "model-index": [{"name": "roberta-large-flash-attention-2-lora-patent-classification", "results": []}]}
peft safetensors generated_from_trainer dataset:patent-classification base_model:roberta-large license:mit region:us