End of training
Browse files- README.md +97 -195
- config.json +117 -0
- model.safetensors +3 -0
- preprocessor_config.json +9 -0
- runs/Sep29_12-25-07_5524cd9e120d/events.out.tfevents.1727614613.5524cd9e120d.6120.0 +3 -0
- training_args.bin +3 -0
README.md
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---
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library_name: transformers
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---
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<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
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[More Information Needed]
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### Training Procedure
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<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
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#### Preprocessing [optional]
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[More Information Needed]
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#### Training Hyperparameters
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- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
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#### Speeds, Sizes, Times [optional]
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[More Information Needed]
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## Evaluation
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### Testing Data, Factors & Metrics
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#### Testing Data
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[More Information Needed]
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#### Factors
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<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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[More Information Needed]
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#### Metrics
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[More Information Needed]
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### Results
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[More Information Needed]
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#### Summary
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## Model Examination [optional]
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<!-- Relevant interpretability work for the model goes here -->
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[More Information Needed]
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## Environmental Impact
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<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
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Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
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- **Hardware Type:** [More Information Needed]
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- **Hours used:** [More Information Needed]
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- **Cloud Provider:** [More Information Needed]
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- **Compute Region:** [More Information Needed]
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- **Carbon Emitted:** [More Information Needed]
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## Technical Specifications [optional]
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### Model Architecture and Objective
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[More Information Needed]
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### Compute Infrastructure
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#### Hardware
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#### Software
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## Citation [optional]
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<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
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**BibTeX:**
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[More Information Needed]
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**APA:**
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[More Information Needed]
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## Glossary [optional]
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<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
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[More Information Needed]
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## More Information [optional]
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[More Information Needed]
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## Model Card Authors [optional]
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## Model Card Contact
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[More Information Needed]
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---
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library_name: transformers
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license: apache-2.0
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base_model: Samuael/geez-asr
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tags:
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- generated_from_trainer
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datasets:
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- alffa_amharic
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metrics:
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- wer
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model-index:
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- name: ethiopic-asr
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results:
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- task:
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name: Automatic Speech Recognition
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type: automatic-speech-recognition
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dataset:
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name: alffa_amharic
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type: alffa_amharic
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config: clean
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split: None
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args: clean
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metrics:
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- name: Wer
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type: wer
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value: 0.14692601597777005
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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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# ethiopic-asr
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This model is a fine-tuned version of [Samuael/geez-asr](https://huggingface.co/Samuael/geez-asr) on the alffa_amharic dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1301
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- Wer: 0.1469
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- Phoneme Cer: 0.0296
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- Cer: 0.0416
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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: 3e-05
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- train_batch_size: 8
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- eval_batch_size: 8
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- seed: 42
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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: 100
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- num_epochs: 1
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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 | Phoneme Cer | Cer |
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|:-------------:|:------:|:----:|:---------------:|:------:|:-----------:|:------:|
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| No log | 0.0442 | 200 | 3.2216 | 1.0 | 1.0 | 1.0 |
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| No log | 0.0883 | 400 | 3.1164 | 1.0 | 1.0 | 1.0 |
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| 4.1769 | 0.1325 | 600 | 0.9628 | 0.5476 | 0.1141 | 0.1609 |
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| 4.1769 | 0.1767 | 800 | 0.3181 | 0.2150 | 0.0430 | 0.0607 |
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| 0.8455 | 0.2208 | 1000 | 0.2195 | 0.1759 | 0.0353 | 0.0503 |
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| 0.8455 | 0.2650 | 1200 | 0.1913 | 0.1846 | 0.0365 | 0.0520 |
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| 0.8455 | 0.3092 | 1400 | 0.1699 | 0.1591 | 0.0322 | 0.0454 |
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| 0.2929 | 0.3534 | 1600 | 0.1603 | 0.1572 | 0.0316 | 0.0442 |
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| 0.2929 | 0.3975 | 1800 | 0.1503 | 0.1567 | 0.0315 | 0.0442 |
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| 0.2392 | 0.4417 | 2000 | 0.1476 | 0.1587 | 0.0318 | 0.0446 |
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| 0.2392 | 0.4859 | 2200 | 0.1449 | 0.1565 | 0.0312 | 0.0438 |
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| 0.2392 | 0.5300 | 2400 | 0.1409 | 0.1537 | 0.0308 | 0.0427 |
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| 0.2166 | 0.5742 | 2600 | 0.1395 | 0.1551 | 0.0308 | 0.0428 |
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| 0.2166 | 0.6184 | 2800 | 0.1345 | 0.1469 | 0.0290 | 0.0410 |
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| 0.2068 | 0.6625 | 3000 | 0.1331 | 0.1509 | 0.0297 | 0.0419 |
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| 0.2068 | 0.7067 | 3200 | 0.1346 | 0.1518 | 0.0301 | 0.0421 |
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| 0.2068 | 0.7509 | 3400 | 0.1335 | 0.1507 | 0.0303 | 0.0426 |
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| 0.2037 | 0.7951 | 3600 | 0.1312 | 0.1471 | 0.0297 | 0.0415 |
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| 0.2037 | 0.8392 | 3800 | 0.1303 | 0.1438 | 0.0289 | 0.0406 |
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| 0.1985 | 0.8834 | 4000 | 0.1300 | 0.1457 | 0.0292 | 0.0410 |
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| 0.1985 | 0.9276 | 4200 | 0.1303 | 0.1471 | 0.0295 | 0.0414 |
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| 0.1985 | 0.9717 | 4400 | 0.1301 | 0.1469 | 0.0296 | 0.0416 |
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### Framework versions
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- Transformers 4.45.1
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- Pytorch 2.4.1+cu121
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- Datasets 3.0.1
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- Tokenizers 0.20.0
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config.json
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{
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"_name_or_path": "Samuael/geez-asr",
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"activation_dropout": 0.0,
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"adapter_attn_dim": null,
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"adapter_kernel_size": 3,
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"adapter_stride": 2,
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"add_adapter": false,
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"apply_spec_augment": true,
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"architectures": [
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"Wav2Vec2ForCTC"
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],
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"attention_dropout": 0.1,
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"bos_token_id": 1,
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"classifier_proj_size": 256,
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"codevector_dim": 768,
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"contrastive_logits_temperature": 0.1,
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"conv_bias": true,
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"conv_dim": [
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512,
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],
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"conv_kernel": [
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],
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"conv_stride": [
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],
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"ctc_loss_reduction": "mean",
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"ctc_zero_infinity": false,
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"diversity_loss_weight": 0.1,
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"do_stable_layer_norm": true,
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"eos_token_id": 2,
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"feat_extract_activation": "gelu",
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"feat_extract_dropout": 0.0,
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"feat_extract_norm": "layer",
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"feat_proj_dropout": 0.1,
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"feat_quantizer_dropout": 0.0,
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"final_dropout": 0.0,
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"gradient_checkpointing": false,
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"hidden_act": "gelu",
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"hidden_dropout": 0.1,
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"hidden_size": 1024,
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"initializer_range": 0.02,
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"intermediate_size": 4096,
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"layer_norm_eps": 1e-05,
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"layerdrop": 0.1,
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"mask_channel_length": 10,
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"mask_channel_min_space": 1,
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"mask_channel_other": 0.0,
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"mask_channel_prob": 0.0,
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"mask_channel_selection": "static",
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"mask_feature_length": 10,
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"mask_feature_min_masks": 0,
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71 |
+
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
95 |
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|
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|
97 |
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],
|
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"tdnn_dim": [
|
99 |
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|
100 |
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|
101 |
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102 |
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|
103 |
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|
105 |
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|
106 |
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|
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|
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|
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|
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|
115 |
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|
116 |
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|
117 |
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}
|
model.safetensors
ADDED
@@ -0,0 +1,3 @@
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|
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|
1 |
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version https://git-lfs.github.com/spec/v1
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size 1261967380
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preprocessor_config.json
ADDED
@@ -0,0 +1,9 @@
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|
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|
1 |
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{
|
2 |
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"do_normalize": true,
|
3 |
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"feature_extractor_type": "Wav2Vec2FeatureExtractor",
|
4 |
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"feature_size": 1,
|
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"padding_side": "right",
|
6 |
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"padding_value": 0.0,
|
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"return_attention_mask": false,
|
8 |
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"sampling_rate": 16000
|
9 |
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}
|
runs/Sep29_12-25-07_5524cd9e120d/events.out.tfevents.1727614613.5524cd9e120d.6120.0
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@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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oid sha256:187a2df814160f99373d5b670574e5692f5b42277659c6ba455cbdcb787604aa
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size 18203
|
training_args.bin
ADDED
@@ -0,0 +1,3 @@
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|
1 |
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version https://git-lfs.github.com/spec/v1
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oid sha256:c0749f892af850fca426c4d4e14d9fe198a6e5db61e2d259e286a0948567e1e6
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size 5240
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