Model save

README.md

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+---
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+model-index:
+- name: AV_MAE_LAVDF_noCL_new
+  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. -->
+
+# AV_MAE_LAVDF_noCL_new
+
+This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4787
+- Accuracy: 0.9386
+- F1: 0.9383
+
+## 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: 5e-05
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- training_steps: 19370
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|
+| 0.7045        | 0.38  | 7354  | 0.5170          | 0.9184   | 0.9176 |
+| 0.3623        | 1.38  | 14710 | 0.4973          | 0.9355   | 0.9351 |
+| 0.0321        | 2.24  | 19370 | 0.4787          | 0.9386   | 0.9383 |
+
+
+### Framework versions
+
+- Transformers 4.37.2
+- Pytorch 2.2.1+cu118
+- Datasets 2.18.0
+- Tokenizers 0.15.1