---
license: mit
base_model: minoosh/finetuned_roberta-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: finetuned_ieroberta-base_on_shEMO_transcripts
  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. -->

# finetuned_ieroberta-base_on_shEMO_transcripts

This model is a fine-tuned version of [minoosh/finetuned_roberta-base-uncased](https://huggingface.co/minoosh/finetuned_roberta-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1943
- Accuracy: 0.5933

## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.3824        | 1.0   | 75   | 1.1850          | 0.5967   |
| 1.1196        | 2.0   | 150  | 0.9580          | 0.6533   |
| 1.0229        | 3.0   | 225  | 0.8937          | 0.6767   |
| 0.8293        | 4.0   | 300  | 0.9288          | 0.6767   |
| 0.7624        | 5.0   | 375  | 0.8706          | 0.6867   |
| 0.6093        | 6.0   | 450  | 0.9811          | 0.68     |
| 0.5163        | 7.0   | 525  | 1.0072          | 0.66     |
| 0.4541        | 8.0   | 600  | 1.0485          | 0.6633   |
| 0.3915        | 9.0   | 675  | 1.0788          | 0.66     |
| 0.3513        | 10.0  | 750  | 1.2308          | 0.6633   |
| 0.3011        | 11.0  | 825  | 1.2203          | 0.6767   |
| 0.1669        | 12.0  | 900  | 1.2282          | 0.6567   |
| 0.1987        | 13.0  | 975  | 1.2879          | 0.6467   |
| 0.2169        | 14.0  | 1050 | 1.3021          | 0.6533   |
| 0.1623        | 15.0  | 1125 | 1.3126          | 0.66     |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1