---
library_name: transformers
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
model-index:
- name: roberta-base-sentiment
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# roberta-base-sentiment

This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on a manually labelled sentiment dataset of earnings call transcript sentences.
It achieves the following results on the evaluation set:
- Loss: 0.8190

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.09          | 1.0   | 39   | 1.0853          |
| 1.0329        | 2.0   | 78   | 1.0255          |
| 0.7433        | 3.0   | 117  | 0.8066          |
| 0.7679        | 4.0   | 156  | 0.7961          |
| 0.4994        | 5.0   | 195  | 0.8190          |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.5.0+cu121
- Datasets 3.0.2
- Tokenizers 0.19.1