File size: 2,469 Bytes
88d210e a0b1bd1 88d210e a0b1bd1 88d210e a0b1bd1 88d210e a0b1bd1 88d210e a0b1bd1 88d210e |
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 87 88 |
---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- PolyAI/minds14
metrics:
- wer
model-index:
- name: whisper-tiny-en-minds14
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: 0.2744982290436836
---
<!-- 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-en-minds14
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: 0.5680
- Wer Ortho: 0.2721
- Wer: 0.2745
## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- 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: 500
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|
| 1.4576 | 1.79 | 50 | 0.9286 | 0.3128 | 0.3152 |
| 0.3694 | 3.57 | 100 | 0.5188 | 0.2776 | 0.2774 |
| 0.0466 | 5.36 | 150 | 0.4494 | 0.2640 | 0.2692 |
| 0.008 | 7.14 | 200 | 0.4855 | 0.2782 | 0.2816 |
| 0.0026 | 8.93 | 250 | 0.4892 | 0.2801 | 0.2845 |
| 0.0016 | 10.71 | 300 | 0.5116 | 0.2745 | 0.2774 |
| 0.0004 | 12.5 | 350 | 0.5383 | 0.2770 | 0.2798 |
| 0.0002 | 14.29 | 400 | 0.5471 | 0.2758 | 0.2774 |
| 0.0002 | 16.07 | 450 | 0.5590 | 0.2714 | 0.2733 |
| 0.0001 | 17.86 | 500 | 0.5680 | 0.2721 | 0.2745 |
### Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
|