Update README.md

README.md

@@ -1,65 +1,79 @@
----
-library_name: transformers
-license: mit
-base_model: microsoft/speecht5_tts
-tags:
-- generated_from_trainer
-model-index:
-- name: speecht5_tr_commonvoice_2
-  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. -->
-
-# speecht5_tr_commonvoice_2
-
-This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on the None dataset.
-It achieves the following results on the evaluation set:
-- Loss: 0.5934
-
-## 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-06
-- train_batch_size: 8
-- eval_batch_size: 2
-- seed: 42
-- gradient_accumulation_steps: 8
-- total_train_batch_size: 64
-- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
-- lr_scheduler_type: linear
-- lr_scheduler_warmup_steps: 500
-- training_steps: 4000
-- mixed_precision_training: Native AMP
-
-### Training results
-
-| Training Loss | Epoch  | Step | Validation Loss |
-|:-------------:|:------:|:----:|:---------------:|
-| 0.7533        | 1.2972 | 1000 | 0.6445          |
-| 0.6745        | 2.5945 | 2000 | 0.6106          |
-| 0.6535        | 3.8917 | 3000 | 0.5953          |
-| 0.6593        | 5.1889 | 4000 | 0.5934          |
-
-
-### Framework versions
-
-- Transformers 4.46.3
-- Pytorch 2.5.1+cu124
-- Datasets 3.1.0
-- Tokenizers 0.20.3
+---
+library_name: transformers
+license: mit
+base_model: microsoft/speecht5_tts
+tags:
+- generated_from_trainer
+model-index:
+- name: speecht5_tr_commonvoice_2
+  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. -->
+
+# speecht5_tr_commonvoice_2
+
+This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5934
+
+## Model description
+```python
+import torch
+from transformers import pipeline
+from datasets import load_dataset
+import soundfile as sf
+
+embeddings_dataset = load_dataset("Matthijs/cmu-arctic-xvectors", split="validation")
+speaker_embedding = torch.tensor(embeddings_dataset[7306]["xvector"]).unsqueeze(0)
+
+from transformers import pipeline
+pipe = pipeline("text-to-audio", model="Chan-Y/speecht5_finetuned_tr_commonvoice")
+
+text = "bugün okula erken geldim, çalışmam lazım. çok sıkıcı bir dersim var."
+result = pipe(text, forward_params={"speaker_embeddings": speaker_embedding})
+
+sf.write("speech.wav", result["audio"], samplerate=result["sampling_rate"])
+
+from IPython.display import Audio
+Audio("speech.wav")
+```
+
+## Training and evaluation data
+
+I used [CommonVoice Turkish Corpus 19.0](https://commonvoice.mozilla.org/tr/datasets)
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 1e-06
+- train_batch_size: 8
+- eval_batch_size: 2
+- seed: 42
+- gradient_accumulation_steps: 8
+- total_train_batch_size: 64
+- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 500
+- training_steps: 4000
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss |
+|:-------------:|:------:|:----:|:---------------:|
+| 0.7533        | 1.2972 | 1000 | 0.6445          |
+| 0.6745        | 2.5945 | 2000 | 0.6106          |
+| 0.6535        | 3.8917 | 3000 | 0.5953          |
+| 0.6593        | 5.1889 | 4000 | 0.5934          |
+
+
+### Framework versions
+
+- Transformers 4.46.3
+- Pytorch 2.5.1+cu124
+- Datasets 3.1.0
+- Tokenizers 0.20.3