File size: 2,287 Bytes
9310585 3057a51 9310585 3057a51 9310585 3057a51 9310585 3057a51 e7355ad 9310585 3057a51 9310585 3057a51 9310585 3057a51 9310585 |
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 |
---
language:
- kn
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
metrics:
- wer
model-index:
- name: Whisper Tiny Kn - Bharat Ramanathan
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: google/fleurs
type: google/fleurs
config: kn_in
split: test
metrics:
- type: wer
value: 43.7
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 Tiny Kn - Bharat Ramanathan
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3057
- Wer: 46.3937
## 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: 150
- eval_batch_size: 64
- 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: 3000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4091 | 0.1 | 300 | 1.4915 | 101.5026 |
| 1.1294 | 0.2 | 600 | 1.2845 | 94.7408 |
| 0.5426 | 0.3 | 900 | 0.4621 | 64.2374 |
| 0.4128 | 1.02 | 1200 | 0.3695 | 54.6582 |
| 0.3629 | 1.12 | 1500 | 0.3414 | 52.9677 |
| 0.3321 | 1.22 | 1800 | 0.3249 | 50.3005 |
| 0.3066 | 1.32 | 2100 | 0.3181 | 48.9106 |
| 0.2958 | 2.03 | 2400 | 0.3136 | 47.7836 |
| 0.2883 | 2.13 | 2700 | 0.3055 | 46.6191 |
| 0.2857 | 2.23 | 3000 | 0.3057 | 46.3937 |
### Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2
|