Model save
Browse files- README.md +67 -0
- config.json +52 -0
- generation_config.json +247 -0
- model.safetensors +3 -0
- preprocessor_config.json +14 -0
- runs/Jan02_10-02-32_Edge-Ai/events.out.tfevents.1704160953.Edge-Ai.2152.0 +3 -0
- runs/Jan02_11-34-32_Edge-Ai/events.out.tfevents.1704166472.Edge-Ai.4711.0 +3 -0
- runs/Jan02_13-13-41_Edge-Ai/events.out.tfevents.1704172421.Edge-Ai.5858.0 +3 -0
- runs/Jan02_14-48-30_Edge-Ai/events.out.tfevents.1704178112.Edge-Ai.14153.0 +3 -0
- training_args.bin +3 -0
README.md
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---
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license: apache-2.0
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base_model: openai/whisper-tiny
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tags:
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- generated_from_trainer
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metrics:
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- wer
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model-index:
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- name: whisper-tiny-tw
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# whisper-tiny-tw
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This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.4244
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- Wer: 72.7331
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 1e-05
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- train_batch_size: 4
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- eval_batch_size: 4
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 16
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_steps: 500
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- training_steps: 4000
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Wer |
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|:-------------:|:-----:|:----:|:---------------:|:-------:|
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| 0.3086 | 1.42 | 1000 | 0.4288 | 80.0170 |
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| 0.2124 | 2.84 | 2000 | 0.4129 | 80.4205 |
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| 0.1149 | 4.26 | 3000 | 0.4217 | 76.7042 |
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| 0.0932 | 5.67 | 4000 | 0.4244 | 72.7331 |
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### Framework versions
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- Transformers 4.36.2
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- Pytorch 2.1.2+cu121
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- Datasets 2.16.0
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- Tokenizers 0.15.0
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config.json
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{
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"_name_or_path": "openai/whisper-tiny",
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"activation_dropout": 0.0,
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"activation_function": "gelu",
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"apply_spec_augment": false,
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"architectures": [
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"WhisperForConditionalGeneration"
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],
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"attention_dropout": 0.0,
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"begin_suppress_tokens": [
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220,
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50257
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],
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"bos_token_id": 50257,
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"classifier_proj_size": 256,
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"d_model": 384,
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"decoder_attention_heads": 6,
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"decoder_ffn_dim": 1536,
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"decoder_layerdrop": 0.0,
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"decoder_layers": 4,
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"decoder_start_token_id": 50258,
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"dropout": 0.0,
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"encoder_attention_heads": 6,
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"encoder_ffn_dim": 1536,
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"encoder_layerdrop": 0.0,
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"encoder_layers": 4,
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"eos_token_id": 50257,
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"forced_decoder_ids": null,
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"init_std": 0.02,
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"is_encoder_decoder": true,
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"mask_feature_length": 10,
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"mask_feature_min_masks": 0,
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"mask_feature_prob": 0.0,
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"mask_time_length": 10,
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"mask_time_min_masks": 2,
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"mask_time_prob": 0.05,
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"max_length": 448,
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"max_source_positions": 1500,
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"max_target_positions": 448,
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"median_filter_width": 7,
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"model_type": "whisper",
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"num_hidden_layers": 4,
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"num_mel_bins": 80,
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"pad_token_id": 50257,
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"scale_embedding": false,
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"suppress_tokens": [],
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"torch_dtype": "float32",
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"transformers_version": "4.36.2",
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"use_cache": true,
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"use_weighted_layer_sum": false,
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"vocab_size": 51865
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}
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generation_config.json
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