Training in progress, step 1000

README.md

@@ -1,51 +1,64 @@
----
-license: mit
-base_model: microsoft/speecht5_tts
-tags:
-- generated_from_trainer
-model-index:
-- name: speecht5_finetuned_hindi_mono
-  results: []
----
-
-
-# speecht5_finetuned_hindi_mono
-
-This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on the Indic TTS Hindi dataset.
-It achieves the following results on the evaluation set:
-- Loss: 0.4357
-
-
-## Training procedure
-
-### Training hyperparameters
-
-The following hyperparameters were used during training:
-- learning_rate: 1e-05
-- train_batch_size: 4
-- eval_batch_size: 2
-- seed: 42
-- gradient_accumulation_steps: 8
-- total_train_batch_size: 32
-- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
-- 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 |
-|:-------------:|:-------:|:----:|:---------------:|
-| 0.5391        | 4.3549  | 1000 | 0.4788          |
-| 0.4991        | 8.7099  | 2000 | 0.4492          |
-| 0.4851        | 13.0648 | 3000 | 0.4367          |
-| 0.4859        | 17.4197 | 4000 | 0.4357          |
-
-
-### Framework versions
-
-- Transformers 4.43.3
-- Pytorch 2.4.0+cu118
-- Datasets 3.0.1
-- Tokenizers 0.19.1
+---
+license: mit
+base_model: microsoft/speecht5_tts
+tags:
+- generated_from_trainer
+model-index:
+- name: speecht5_finetuned_hindi_mono
+  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_finetuned_hindi_mono
+
+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: 0.4357
+
+## 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-05
+- train_batch_size: 4
+- eval_batch_size: 2
+- seed: 42
+- gradient_accumulation_steps: 8
+- total_train_batch_size: 32
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- 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 |
+|:-------------:|:-------:|:----:|:---------------:|
+| 0.5391        | 4.3549  | 1000 | 0.4788          |
+| 0.4991        | 8.7099  | 2000 | 0.4492          |
+| 0.4851        | 13.0648 | 3000 | 0.4367          |
+| 0.4859        | 17.4197 | 4000 | 0.4357          |
+
+
+### Framework versions
+
+- Transformers 4.43.3
+- Pytorch 2.4.0+cu118
+- Datasets 3.0.1
+- Tokenizers 0.19.1

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