peft safetensors generated_from_trainer dataset:patent-classification base_model:roberta-large license:mit region:us
---
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-2e-4
  results: []
---

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# roberta-large-flash-attention-2-lora-patent-classification-2e-4

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: 0.8264
- Accuracy: 0.659
- Precision Macro: 0.6268
- Recall Macro: 0.6433
- F1-score Macro: 0.6295

## 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: 0.0002
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------------:|:------------:|:--------------:|
| 0.8107        | 1.0   | 4167  | 0.9531          | 0.5096   | 0.6495          | 0.4554       | 0.4831         |
| 0.7105        | 2.0   | 8334  | 0.8408          | 0.6426   | 0.6307          | 0.6261       | 0.6208         |
| 0.6299        | 3.0   | 12501 | 0.8264          | 0.659    | 0.6268          | 0.6433       | 0.6295         |


### 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