End of training

README.md

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+---
+library_name: transformers
+license: mit
+base_model: microsoft/speecht5_tts
+tags:
+- generated_from_trainer
+datasets:
+- common_voice_22_0
+model-index:
+- name: speecht5_english
+  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_english
+
+This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on the common_voice_22_0 dataset.
+It achieves the following results on the evaluation set:
+- eval_loss: 0.5857
+- eval_runtime: 1.8838
+- eval_samples_per_second: 50.962
+- eval_steps_per_second: 6.37
+- epoch: 285.7407
+- step: 4000
+
+## 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: 0.0001
+- train_batch_size: 16
+- eval_batch_size: 8
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 64
+- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: cosine_with_restarts
+- lr_scheduler_warmup_steps: 500
+- training_steps: 6000
+- mixed_precision_training: Native AMP
+
+### Framework versions
+
+- Transformers 4.57.3
+- Pytorch 2.9.1+cu128
+- Datasets 2.20.0
+- Tokenizers 0.22.2

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