File size: 2,385 Bytes
19bac4a 6bad00f 19bac4a 6bad00f 19bac4a 6bad00f 19bac4a 6bad00f 19bac4a |
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 86 |
---
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- PolyAI/minds14
metrics:
- wer
model-index:
- name: whisper-tiny-minds14-en_US-test-finetuned
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: PolyAI/minds14
type: PolyAI/minds14
config: en-US
split: train
args: en-US
metrics:
- name: Wer
type: wer
value: 0.26380766731643923
---
<!-- 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-tiny-minds14-en_US-test-finetuned
This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the PolyAI/minds14 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0871
- Wer Ortho: 26.8342
- Wer: 0.2638
## 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: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 50
- training_steps: 4000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|:-------------:|:------:|:----:|:---------------:|:---------:|:------:|
| 0.0021 | 17.86 | 500 | 0.7863 | 26.6304 | 0.2534 |
| 0.0002 | 35.71 | 1000 | 0.8689 | 26.7663 | 0.2612 |
| 0.0001 | 53.57 | 1500 | 0.9230 | 27.2418 | 0.2664 |
| 0.0001 | 71.43 | 2000 | 0.9637 | 27.1739 | 0.2664 |
| 0.0 | 89.29 | 2500 | 0.9977 | 26.9022 | 0.2638 |
| 0.0 | 107.14 | 3000 | 1.0277 | 27.1739 | 0.2664 |
| 0.0 | 125.0 | 3500 | 1.0571 | 27.1739 | 0.2671 |
| 0.0 | 142.86 | 4000 | 1.0871 | 26.8342 | 0.2638 |
### Framework versions
- Transformers 4.38.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.15.2
|