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---
language:
- as
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
- google/fleurs
metrics:
- wer
model-index:
- name: kpriyanshu256/whisper-large-v2-as-600-32-1e-05-bn-Assamese
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 11.0
type: mozilla-foundation/common_voice_11_0
config: as
split: test
args: as
metrics:
- name: Wer
type: wer
value: 17.560007218913555
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: FLEURS
type: google/fleurs
metrics:
- name: Wer
type: wer
value:
---
<!-- 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. -->
# kpriyanshu256/whisper-large-v2-as-600-32-1e-05-bn-Assamese
This model is a fine-tuned version of [kpriyanshu256/whisper-large-v2-as-600-32-1e-05-bn](https://huggingface.co/kpriyanshu256/whisper-large-v2-as-600-32-1e-05-bn) on the Common Voice 11.0 and the FLEURS datasets.
It achieves the following results on the evaluation set:
- Loss: 0.2486
- Wer: 17.5600
## 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
- distributed_type: multi-GPU
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 1000
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.1273 | 0.1 | 100 | 0.1737 | 20.8988 |
| 0.0811 | 0.2 | 200 | 0.1739 | 19.0038 |
| 0.0638 | 0.3 | 300 | 0.1823 | 18.4804 |
| 0.0404 | 1.05 | 400 | 0.1893 | 17.1810 |
| 0.0316 | 1.15 | 500 | 0.2067 | 17.0186 |
| 0.027 | 1.25 | 600 | 0.2081 | 17.7405 |
| 0.025 | 2.01 | 700 | 0.2213 | 17.7585 |
| 0.0213 | 2.11 | 800 | 0.2237 | 17.8488 |
| 0.0176 | 2.21 | 900 | 0.2390 | 16.7479 |
| 0.0184 | 2.31 | 1000 | 0.2486 | 17.5600 |
### Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2
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