Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Marathi
whisper
Generated from Trainer
Instructions to use simran14/stt-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use simran14/stt-1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="simran14/stt-1")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("simran14/stt-1") model = AutoModelForSpeechSeq2Seq.from_pretrained("simran14/stt-1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Download README.md from simran14/stt-1: direct link, hf CLI and curl.
- Browser
- Download file 1.45 kB
-
https://huggingface.co/simran14/stt-1/resolve/main/README.md
- Command line
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hf download hf://simran14/stt-1/README.md
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curl -L -o README.md https://huggingface.co/simran14/stt-1/resolve/main/README.md
1.45 kB
| library_name: transformers | |
| language: | |
| - mr | |
| license: apache-2.0 | |
| base_model: openai/whisper-small | |
| tags: | |
| - generated_from_trainer | |
| datasets: | |
| - mozilla-foundation/common_voice_17_0 | |
| model-index: | |
| - name: mr stt 1st finetuning | |
| 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. --> | |
| # mr stt 1st finetuning | |
| This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 17.0 dataset. | |
| It achieves the following results on the evaluation set: | |
| - eval_loss: 0.5771 | |
| - eval_wer: 25.9487 | |
| - eval_runtime: 958.3173 | |
| - eval_samples_per_second: 1.637 | |
| - eval_steps_per_second: 0.206 | |
| - epoch: 0.6098 | |
| - step: 1000 | |
| ## 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: 5e-07 | |
| - 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: 100 | |
| - num_epochs: 2 | |
| - mixed_precision_training: Native AMP | |
| ### Framework versions | |
| - Transformers 4.45.0.dev0 | |
| - Pytorch 2.2.1+cu121 | |
| - Datasets 3.0.0 | |
| - Tokenizers 0.19.1 | |