End of training

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: distilbert/distilbert-base-uncased
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: finetuning-sentiment-model-distil-finalVersion
+  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. -->
+
+# finetuning-sentiment-model-distil-finalVersion
+
+This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.6034
+- Precision Negative: 0.8333
+- Recall Negative: 0.5556
+- F1 Negative: 0.6667
+- Precision Neutral: 0.75
+- Recall Neutral: 0.9
+- F1 Neutral: 0.8182
+- Precision Positive: 0.8462
+- Recall Positive: 0.7857
+- F1 Positive: 0.8148
+- Accuracy: 0.7907
+- Confusion Matrix: [[20, 14, 2], [2, 72, 6], [2, 10, 44]]
+
+## 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: 32
+- eval_batch_size: 16
+- seed: 42
+- 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: 6
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision Negative | Recall Negative | F1 Negative | Precision Neutral | Recall Neutral | F1 Neutral | Precision Positive | Recall Positive | F1 Positive | Accuracy | Confusion Matrix                       |
+|:-------------:|:-----:|:----:|:---------------:|:------------------:|:---------------:|:-----------:|:-----------------:|:--------------:|:----------:|:------------------:|:---------------:|:-----------:|:--------:|:--------------------------------------:|
+| 0.9478        | 1.0   | 22   | 0.9752          | 0.0                | 0.0             | 0.0         | 0.5064            | 0.9875         | 0.6695     | 0.875              | 0.25            | 0.3889      | 0.5407   | [[0, 35, 1], [0, 79, 1], [0, 42, 14]]  |
+| 0.7207        | 2.0   | 44   | 0.6483          | 0.8667             | 0.3611          | 0.5098      | 0.6847            | 0.95           | 0.7958     | 0.8913             | 0.7321          | 0.8039      | 0.7558   | [[13, 21, 2], [1, 76, 3], [1, 14, 41]] |
+| 0.4066        | 3.0   | 66   | 0.6153          | 0.7586             | 0.6111          | 0.6769      | 0.7308            | 0.95           | 0.8261     | 1.0                | 0.6964          | 0.8211      | 0.7965   | [[22, 14, 0], [4, 76, 0], [3, 14, 39]] |
+| 0.2355        | 4.0   | 88   | 0.6367          | 0.8                | 0.5556          | 0.6557      | 0.7170            | 0.95           | 0.8172     | 0.9756             | 0.7143          | 0.8247      | 0.7907   | [[20, 16, 0], [3, 76, 1], [2, 14, 40]] |
+| 0.1048        | 5.0   | 110  | 0.5976          | 0.8333             | 0.5556          | 0.6667      | 0.75              | 0.9            | 0.8182     | 0.8462             | 0.7857          | 0.8148      | 0.7907   | [[20, 14, 2], [2, 72, 6], [2, 10, 44]] |
+| 0.0745        | 6.0   | 132  | 0.6034          | 0.8333             | 0.5556          | 0.6667      | 0.75              | 0.9            | 0.8182     | 0.8462             | 0.7857          | 0.8148      | 0.7907   | [[20, 14, 2], [2, 72, 6], [2, 10, 44]] |
+
+
+### Framework versions
+
+- Transformers 4.46.3
+- Pytorch 2.5.1+cu121
+- Datasets 3.1.0
+- Tokenizers 0.20.3

runs/Dec07_08-06-04_386f23c91b0c/events.out.tfevents.1733559815.386f23c91b0c.1103.8

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