File size: 4,111 Bytes
cebe2f0 |
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 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 |
---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- common_voice_13_0
metrics:
- wer
model-index:
- name: whisper-small-ne-NP
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice_13_0
type: common_voice_13_0
config: ne-NP
split: test
args: ne-NP
metrics:
- name: Wer
type: wer
value: 57.38758029978587
---
<!-- 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-ne-NP
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the common_voice_13_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6005
- Wer: 57.3876
## 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: 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: 4000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.9935 | 0.17 | 100 | 1.3460 | 91.4347 |
| 0.6624 | 0.35 | 200 | 1.0307 | 85.6531 |
| 0.5002 | 0.52 | 300 | 0.8406 | 77.5161 |
| 0.4426 | 0.7 | 400 | 0.7038 | 76.2313 |
| 0.3063 | 0.87 | 500 | 0.5308 | 71.5203 |
| 0.1949 | 1.05 | 600 | 0.5200 | 66.1670 |
| 0.1974 | 1.22 | 700 | 0.5140 | 65.0964 |
| 0.1734 | 1.4 | 800 | 0.4423 | 67.6660 |
| 0.1619 | 1.57 | 900 | 0.4705 | 62.0985 |
| 0.1697 | 1.75 | 1000 | 0.4676 | 67.0236 |
| 0.1536 | 1.92 | 1100 | 0.4441 | 62.7409 |
| 0.0722 | 2.1 | 1200 | 0.4492 | 58.0300 |
| 0.0674 | 2.27 | 1300 | 0.4597 | 59.9572 |
| 0.0766 | 2.45 | 1400 | 0.4720 | 62.3126 |
| 0.0732 | 2.62 | 1500 | 0.4720 | 60.5996 |
| 0.0737 | 2.8 | 1600 | 0.4704 | 61.0278 |
| 0.0833 | 2.97 | 1700 | 0.4711 | 59.7430 |
| 0.0421 | 3.15 | 1800 | 0.5040 | 60.5996 |
| 0.0444 | 3.32 | 1900 | 0.5096 | 62.5268 |
| 0.0343 | 3.5 | 2000 | 0.5276 | 62.5268 |
| 0.0347 | 3.67 | 2100 | 0.5068 | 57.3876 |
| 0.0326 | 3.85 | 2200 | 0.5143 | 59.3148 |
| 0.0219 | 4.02 | 2300 | 0.5225 | 59.3148 |
| 0.0129 | 4.2 | 2400 | 0.5353 | 59.1006 |
| 0.0159 | 4.37 | 2500 | 0.5639 | 56.9593 |
| 0.0168 | 4.55 | 2600 | 0.5303 | 55.8887 |
| 0.0131 | 4.72 | 2700 | 0.5455 | 58.6724 |
| 0.0122 | 4.9 | 2800 | 0.5548 | 56.5310 |
| 0.0035 | 5.07 | 2900 | 0.5661 | 56.7452 |
| 0.0027 | 5.24 | 3000 | 0.5789 | 57.6017 |
| 0.0034 | 5.42 | 3100 | 0.5887 | 59.1006 |
| 0.0047 | 5.59 | 3200 | 0.5853 | 59.9572 |
| 0.0054 | 5.77 | 3300 | 0.5912 | 58.4582 |
| 0.0042 | 5.94 | 3400 | 0.5862 | 59.3148 |
| 0.0013 | 6.12 | 3500 | 0.5935 | 56.7452 |
| 0.001 | 6.29 | 3600 | 0.5991 | 57.3876 |
| 0.0008 | 6.47 | 3700 | 0.6012 | 57.6017 |
| 0.0014 | 6.64 | 3800 | 0.6002 | 57.8158 |
| 0.001 | 6.82 | 3900 | 0.6006 | 57.8158 |
| 0.0013 | 6.99 | 4000 | 0.6005 | 57.3876 |
### Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0
- Datasets 2.11.0
- Tokenizers 0.13.3
|