---
license: apache-2.0
base_model: minoosh/finetuned_bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: finetuned_iebert-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_iebert-base_on_shEMO_transcripts

This model is a fine-tuned version of [minoosh/finetuned_bert-base-uncased](https://huggingface.co/minoosh/finetuned_bert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3279
- Accuracy: 0.5367

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4217        | 1.0   | 75   | 1.2872          | 0.4933   |
| 1.2468        | 2.0   | 150  | 1.1732          | 0.5433   |
| 1.202         | 3.0   | 225  | 1.0937          | 0.5833   |
| 1.1722        | 4.0   | 300  | 1.1343          | 0.5767   |
| 1.1248        | 5.0   | 375  | 1.0780          | 0.58     |
| 1.0578        | 6.0   | 450  | 1.0778          | 0.59     |
| 0.9632        | 7.0   | 525  | 1.0967          | 0.59     |
| 0.8325        | 8.0   | 600  | 1.1147          | 0.5933   |
| 0.8339        | 9.0   | 675  | 1.1271          | 0.61     |
| 0.7494        | 10.0  | 750  | 1.1886          | 0.59     |
| 0.6416        | 11.0  | 825  | 1.2204          | 0.5833   |
| 0.5611        | 12.0  | 900  | 1.3593          | 0.5567   |
| 0.5421        | 13.0  | 975  | 1.3113          | 0.56     |
| 0.53          | 14.0  | 1050 | 1.3207          | 0.5733   |
| 0.4981        | 15.0  | 1125 | 1.3327          | 0.5567   |


### Framework versions

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