---
library_name: transformers
license: mit
base_model: FacebookAI/roberta-large
tags:
- generated_from_trainer
model-index:
- name: RoBERTa-lifescience-domain
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# RoBERTa-lifescience-domain

This model is a fine-tuned version of [FacebookAI/roberta-large](https://huggingface.co/FacebookAI/roberta-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9681
- Model Preparation Time: 0.0035

## 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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Model Preparation Time |
|:-------------:|:-----:|:----:|:---------------:|:----------------------:|
| No log        | 1.0   | 80   | 1.0417          | 0.0035                 |
| No log        | 2.0   | 160  | 1.0000          | 0.0035                 |
| No log        | 3.0   | 240  | 0.9877          | 0.0035                 |
| 0.9263        | 4.0   | 320  | 0.9724          | 0.0035                 |
| 0.9263        | 5.0   | 400  | 0.9860          | 0.0035                 |


### Framework versions

- Transformers 4.52.4
- Pytorch 2.7.1+cu126
- Datasets 3.6.0
- Tokenizers 0.21.1