File size: 2,103 Bytes
62a9a9e 8c1f29b 62a9a9e 8c1f29b 62a9a9e 8c1f29b 62a9a9e 8c1f29b 62a9a9e |
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 |
---
language:
- hi
license: apache-2.0
tags:
- generated_from_trainer
base_model: Aakali/whisper-medium-hi
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper medium-translate Hi - Aa
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: Common Voice 11.0
type: mozilla-foundation/common_voice_11_0
args: 'config: hi, split: test'
metrics:
- type: wer
value: 48.11612382957753
name: Wer
---
<!-- 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 medium-translate Hi - Aa
This model is a fine-tuned version of [Aakali/whisper-medium-hi](https://huggingface.co/Aakali/whisper-medium-hi) on the Common Voice 11.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9904
- Wer: 48.1161
## 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: 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: 5000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-------:|:----:|:---------------:|:-------:|
| 0.1405 | 2.4450 | 1000 | 0.7580 | 51.5075 |
| 0.0245 | 4.8900 | 2000 | 0.8571 | 51.4000 |
| 0.0026 | 7.3350 | 3000 | 0.9280 | 48.3132 |
| 0.0011 | 9.7800 | 4000 | 0.9673 | 47.6457 |
| 0.0006 | 12.2249 | 5000 | 0.9904 | 48.1161 |
### Framework versions
- Transformers 4.41.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
|