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---
language:
- en
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- St4n/new-2
metrics:
- wer
model-index:
- name: Whisper Small En - Stan
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: new-2
type: St4n/new-2
config: default
split: None
args: 'config: en, split: test'
metrics:
- name: Wer
type: wer
value: 8.513708513708513
---
<!-- 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 Small En - Stan
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the new-2 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1269
- Wer: 8.5137
## 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: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- training_steps: 6000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 0.0026 | 30.77 | 200 | 0.0885 | 3.0303 |
| 0.0001 | 61.54 | 400 | 0.1035 | 8.8023 |
| 0.0 | 92.31 | 600 | 0.1082 | 8.8023 |
| 0.0 | 123.08 | 800 | 0.1111 | 8.5137 |
| 0.0 | 153.85 | 1000 | 0.1128 | 8.5137 |
| 0.0 | 184.62 | 1200 | 0.1143 | 8.5137 |
| 0.0 | 215.38 | 1400 | 0.1153 | 8.5137 |
| 0.0 | 246.15 | 1600 | 0.1162 | 8.5137 |
| 0.0 | 276.92 | 1800 | 0.1169 | 8.5137 |
| 0.0 | 307.69 | 2000 | 0.1176 | 8.5137 |
| 0.0 | 338.46 | 2200 | 0.1196 | 8.5137 |
| 0.0 | 369.23 | 2400 | 0.1211 | 8.5137 |
| 0.0 | 400.0 | 2600 | 0.1217 | 8.5137 |
| 0.0 | 430.77 | 2800 | 0.1221 | 8.5137 |
| 0.0 | 461.54 | 3000 | 0.1224 | 8.5137 |
| 0.0 | 492.31 | 3200 | 0.1225 | 8.5137 |
| 0.0 | 523.08 | 3400 | 0.1227 | 8.5137 |
| 0.0 | 553.85 | 3600 | 0.1228 | 8.5137 |
| 0.0 | 584.62 | 3800 | 0.1229 | 8.5137 |
| 0.0 | 615.38 | 4000 | 0.1230 | 8.5137 |
| 0.0 | 646.15 | 4200 | 0.1253 | 8.5137 |
| 0.0 | 676.92 | 4400 | 0.1263 | 8.5137 |
| 0.0 | 707.69 | 4600 | 0.1265 | 8.5137 |
| 0.0 | 738.46 | 4800 | 0.1267 | 8.5137 |
| 0.0 | 769.23 | 5000 | 0.1266 | 8.5137 |
| 0.0 | 800.0 | 5200 | 0.1267 | 8.5137 |
| 0.0 | 830.77 | 5400 | 0.1267 | 8.5137 |
| 0.0 | 861.54 | 5600 | 0.1269 | 8.5137 |
| 0.0 | 892.31 | 5800 | 0.1269 | 8.5137 |
| 0.0 | 923.08 | 6000 | 0.1269 | 8.5137 |
### Framework versions
- Transformers 4.39.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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