---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: whisper-base-finetuned-bmd
  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. -->

# whisper-base-finetuned-bmd

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3900
- Accuracy: 0.3235
- F1: 0.3095
- Precision: 0.4512
- Recall: 0.3235
- Sensitivity: 0.3235

## 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: 3e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 15

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy | F1     | Precision | Recall | Sensitivity |
|:-------------:|:-------:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|:-----------:|
| No log        | 0.8571  | 3    | 1.1235          | 0.2647   | 0.1108 | 0.0701    | 0.2647 | 0.2647      |
| No log        | 2.0     | 7    | 1.1253          | 0.2647   | 0.1108 | 0.0701    | 0.2647 | 0.2647      |
| 1.0608        | 2.8571  | 10   | 1.1178          | 0.2647   | 0.1162 | 0.0744    | 0.2647 | 0.2647      |
| 1.0608        | 4.0     | 14   | 1.1206          | 0.2941   | 0.1740 | 0.4886    | 0.2941 | 0.2941      |
| 1.0608        | 4.8571  | 17   | 1.1225          | 0.2941   | 0.2083 | 0.3475    | 0.2941 | 0.2941      |
| 0.9214        | 6.0     | 21   | 1.1167          | 0.4412   | 0.4108 | 0.5259    | 0.4412 | 0.4412      |
| 0.9214        | 6.8571  | 24   | 1.0754          | 0.5      | 0.4625 | 0.4954    | 0.5    | 0.5         |
| 0.9214        | 8.0     | 28   | 1.1578          | 0.4118   | 0.3959 | 0.4304    | 0.4118 | 0.4118      |
| 0.6179        | 8.8571  | 31   | 1.2143          | 0.3824   | 0.3663 | 0.4120    | 0.3824 | 0.3824      |
| 0.6179        | 10.0    | 35   | 1.3170          | 0.4118   | 0.4169 | 0.5174    | 0.4118 | 0.4118      |
| 0.6179        | 10.8571 | 38   | 1.3484          | 0.3529   | 0.3484 | 0.4777    | 0.3529 | 0.3529      |
| 0.3513        | 12.0    | 42   | 1.3904          | 0.3235   | 0.3095 | 0.4512    | 0.3235 | 0.3235      |
| 0.3513        | 12.8571 | 45   | 1.3900          | 0.3235   | 0.3095 | 0.4512    | 0.3235 | 0.3235      |


### Framework versions

- Transformers 4.46.2
- Pytorch 2.5.0+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3