File size: 1,977 Bytes
0733bae b82f8a7 1b8dc92 0733bae d2e7fed 0733bae d2e7fed 0733bae d2e7fed 1b8dc92 d2e7fed 0733bae c17e695 0733bae a9dd21f 1b8dc92 d2e7fed 1b8dc92 4dcf62c 0733bae d2e7fed |
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 |
---
license: apache-2.0
tags:
- generated_from_trainer
base_model: openai/whisper-small.en
metrics:
- wer
model-index:
- name: whisper-small-hi
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-small-hi
This model is a fine-tuned version of [openai/whisper-small.en](https://huggingface.co/openai/whisper-small.en) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0002
- Wer: 1.5152
## 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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 1000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 1.1465 | 25.0 | 100 | 1.1124 | 9.6970 |
| 0.4228 | 50.0 | 200 | 0.4547 | 2.4242 |
| 0.0555 | 75.0 | 300 | 0.0459 | 1.8182 |
| 0.0022 | 100.0 | 400 | 0.0022 | 1.8182 |
| 0.0007 | 125.0 | 500 | 0.0008 | 1.5152 |
| 0.0004 | 150.0 | 600 | 0.0005 | 1.5152 |
| 0.0003 | 175.0 | 700 | 0.0003 | 1.5152 |
| 0.0002 | 200.0 | 800 | 0.0003 | 1.5152 |
| 0.0002 | 225.0 | 900 | 0.0003 | 1.5152 |
| 0.0002 | 250.0 | 1000 | 0.0002 | 1.5152 |
### Framework versions
- Transformers 4.41.0
- Pytorch 2.2.0a0+81ea7a4
- Datasets 2.19.1
- Tokenizers 0.19.1
|