End of training

README.md

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+---
+license: mit
+base_model: microsoft/MiniLM-L12-H384-uncased
+tags:
+- generated_from_trainer
+datasets:
+- emotion
+metrics:
+- f1
+model-index:
+- name: minisss
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: emotion
+      type: emotion
+      config: split
+      split: validation
+      args: split
+    metrics:
+    - name: F1
+      type: f1
+      value: 0.9361370380020481
+---
+
+<!-- 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. -->
+
+# minisss
+
+This model is a fine-tuned version of [microsoft/MiniLM-L12-H384-uncased](https://huggingface.co/microsoft/MiniLM-L12-H384-uncased) on the emotion dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1791
+- F1: 0.9361
+
+## 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: 64
+- eval_batch_size: 64
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 5
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:------:|
+| 1.1818        | 1.0   | 250  | 0.8298          | 0.5948 |
+| 0.6392        | 2.0   | 500  | 0.3998          | 0.9005 |
+| 0.3246        | 3.0   | 750  | 0.2472          | 0.9301 |
+| 0.2151        | 4.0   | 1000 | 0.1937          | 0.9341 |
+| 0.1707        | 5.0   | 1250 | 0.1791          | 0.9361 |
+
+
+### Framework versions
+
+- Transformers 4.38.2
+- Pytorch 2.2.1+cu121
+- Datasets 2.18.0
+- Tokenizers 0.15.2

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