HamzaSidhu786
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urdu_text_to_speech_tts
Browse files- README.md +78 -199
- generation_config.json +9 -0
- model.safetensors +1 -1
- runs/Jul28_15-45-47_Hamza/events.out.tfevents.1722163552.Hamza.5788.1 +2 -2
README.md
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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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#### 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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#### Factors
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#### Metrics
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### Results
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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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### 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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**APA:**
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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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## 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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license: mit
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base_model: microsoft/speecht5_tts
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tags:
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- generated_from_trainer
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model-index:
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- name: urdu_text_to_speech_tts
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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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# urdu_text_to_speech_tts
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This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.4936
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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: 8
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- eval_batch_size: 2
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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: 500
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- num_epochs: 20
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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 |
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|:-------------:|:-----:|:----:|:---------------:|
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| 0.6365 | 1.0 | 486 | 0.5707 |
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| 0.6045 | 2.0 | 972 | 0.5319 |
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| 0.591 | 3.0 | 1458 | 0.5265 |
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| 0.5711 | 4.0 | 1944 | 0.5178 |
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| 0.5528 | 5.0 | 2430 | 0.5142 |
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| 0.5335 | 6.0 | 2916 | 0.5073 |
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| 0.5316 | 7.0 | 3402 | 0.5015 |
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| 0.5308 | 8.0 | 3888 | 0.4992 |
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| 0.5381 | 9.0 | 4374 | 0.5022 |
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| 0.5292 | 10.0 | 4860 | 0.4977 |
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| 0.5242 | 11.0 | 5346 | 0.4975 |
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| 0.5129 | 12.0 | 5832 | 0.4970 |
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| 0.5122 | 13.0 | 6318 | 0.4937 |
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| 0.5329 | 14.0 | 6804 | 0.4943 |
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| 0.5189 | 15.0 | 7290 | 0.4921 |
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| 0.5164 | 16.0 | 7776 | 0.4946 |
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| 0.5097 | 17.0 | 8262 | 0.4931 |
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| 0.5858 | 18.0 | 8748 | 0.4948 |
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| 0.5128 | 19.0 | 9234 | 0.4936 |
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| 0.5203 | 20.0 | 9720 | 0.4936 |
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### Framework versions
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- Transformers 4.42.3
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- Pytorch 2.3.1+cu121
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- Datasets 2.20.0
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- Tokenizers 0.19.1
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generation_config.json
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{
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"_from_model_config": true,
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"bos_token_id": 0,
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"decoder_start_token_id": 2,
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"eos_token_id": 2,
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"max_length": 1876,
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"pad_token_id": 1,
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"transformers_version": "4.42.3"
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}
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model.safetensors
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runs/Jul28_15-45-47_Hamza/events.out.tfevents.1722163552.Hamza.5788.1
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