Model save

README.md

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+---
+library_name: transformers
+tags:
+- generated_from_trainer
+datasets:
+- voxceleb
+metrics:
+- accuracy
+model-index:
+- name: aam-len3-bs256-lr1e-3
+  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. -->
+
+# aam-len3-bs256-lr1e-3
+
+This model is a fine-tuned version of [](https://huggingface.co/) on the voxceleb dataset.
+It achieves the following results on the evaluation set:
+- Loss: nan
+- Accuracy: 0.0005
+
+## 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: 0.001
+- train_batch_size: 256
+- eval_batch_size: 1
+- seed: 914
+- optimizer: Use 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_ratio: 0.1
+- num_epochs: 10.0
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 7.6771        | 1.0   | 523  | 6.7010          | 0.6003   |
+| 3.5879        | 2.0   | 1046 | 1.9993          | 0.9141   |
+| 1.9536        | 3.0   | 1569 | 0.8234          | 0.9607   |
+| 1.5008        | 4.0   | 2092 | 0.6434          | 0.9617   |
+| 0.0           | 5.0   | 2615 | nan             | 0.0005   |
+| 0.0           | 6.0   | 3138 | nan             | 0.0005   |
+| 0.0           | 7.0   | 3661 | nan             | 0.0005   |
+| 0.0           | 8.0   | 4184 | nan             | 0.0005   |
+| 0.0           | 9.0   | 4707 | nan             | 0.0005   |
+| 0.0           | 10.0  | 5230 | nan             | 0.0005   |
+
+
+### Framework versions
+
+- Transformers 4.48.3
+- Pytorch 2.0.0+cu117
+- Datasets 3.2.0
+- Tokenizers 0.21.0

model.safetensors

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