Instructions to use SlothBot/home_workstation_ASR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SlothBot/home_workstation_ASR with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="SlothBot/home_workstation_ASR")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("SlothBot/home_workstation_ASR") model = AutoModelForSpeechSeq2Seq.from_pretrained("SlothBot/home_workstation_ASR", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| license: apache-2.0 | |
| base_model: openai/whisper-small | |
| tags: | |
| - generated_from_trainer | |
| metrics: | |
| - wer | |
| model-index: | |
| - name: home_workstation_ASR | |
| 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. --> | |
| # home_workstation_ASR | |
| 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: 0.3540 | |
| - Wer Ortho: 20.1592 | |
| - Wer: 15.1297 | |
| ## 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: 32 | |
| - eval_batch_size: 16 | |
| - seed: 42 | |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
| - lr_scheduler_type: constant_with_warmup | |
| - lr_scheduler_warmup_steps: 50 | |
| - training_steps: 4000 | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer | | |
| |:-------------:|:-----:|:----:|:---------------:|:---------:|:-------:| | |
| | 0.232 | 0.9 | 1000 | 0.3209 | 21.7751 | 16.8164 | | |
| | 0.1153 | 1.8 | 2000 | 0.3150 | 20.7647 | 15.7552 | | |
| | 0.0653 | 2.7 | 3000 | 0.3327 | 20.2443 | 15.2927 | | |
| | 0.032 | 3.6 | 4000 | 0.3540 | 20.1592 | 15.1297 | | |
| ### Framework versions | |
| - Transformers 4.34.0 | |
| - Pytorch 2.1.0+cu121 | |
| - Datasets 2.14.5 | |
| - Tokenizers 0.14.1 | |