Model save

README.md

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+---
+license: apache-2.0
+base_model: albert-base-v2
+tags:
+- generated_from_trainer
+datasets:
+- emotion
+metrics:
+- accuracy
+model-index:
+- name: ALBERT_trainer_emotion
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: emotion
+      type: emotion
+      config: split
+      split: validation
+      args: split
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.927
+---
+
+<!-- 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. -->
+
+# ALBERT_trainer_emotion
+
+This model is a fine-tuned version of [albert-base-v2](https://huggingface.co/albert-base-v2) on the emotion dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3559
+- Accuracy: 0.927
+
+## 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: 2e-05
+- train_batch_size: 20
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 7
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.1217        | 1.0   | 800  | 0.1936          | 0.93     |
+| 0.1054        | 2.0   | 1600 | 0.2105          | 0.9305   |
+| 0.0893        | 3.0   | 2400 | 0.2199          | 0.933    |
+| 0.0751        | 4.0   | 3200 | 0.2412          | 0.9375   |
+| 0.0608        | 5.0   | 4000 | 0.2853          | 0.932    |
+| 0.0342        | 6.0   | 4800 | 0.3575          | 0.9315   |
+| 0.025         | 7.0   | 5600 | 0.3698          | 0.931    |
+
+
+### Framework versions
+
+- Transformers 4.38.2
+- Pytorch 2.2.1+cu121
+- Datasets 2.18.0
+- Tokenizers 0.15.2

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