File size: 2,136 Bytes
d48aa28 e74b38e d48aa28 e74b38e d48aa28 2f8b7f9 d48aa28 e74b38e d48aa28 8df9e17 d48aa28 2f8b7f9 d48aa28 2f8b7f9 abfb910 d48aa28 177b3ee 2f8b7f9 d48aa28 2f8b7f9 d48aa28 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 |
---
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- audiofolder
metrics:
- wer
model-index:
- name: Whisper Small Seneca
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: audiofolder
type: audiofolder
config: default
split: train
args: default
metrics:
- name: Wer
type: wer
value: 27.49828990734407
---
<!-- 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 Seneca
This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the audiofolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5983
- Wer: 27.4983
## 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: 16
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 7768
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.1151 | 3.01 | 1000 | 0.4013 | 31.8326 |
| 0.0185 | 6.02 | 2000 | 0.4796 | 30.1660 |
| 0.0062 | 9.03 | 3000 | 0.5143 | 30.0417 |
| 0.0022 | 12.04 | 4000 | 0.5469 | 28.6301 |
| 0.0004 | 16.01 | 5000 | 0.5695 | 27.9522 |
| 0.0001 | 19.01 | 6000 | 0.5891 | 27.5294 |
| 0.0002 | 22.02 | 7000 | 0.5983 | 27.4983 |
### Framework versions
- Transformers 4.25.1
- Pytorch 1.13.1+cu117
- Datasets 2.8.0
- Tokenizers 0.13.2
|