electra-5-epoch-sentiment

README.md

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+---
+license: apache-2.0
+base_model: google/electra-small-discriminator
+tags:
+- generated_from_trainer
+datasets:
+- tweet_eval
+metrics:
+- accuracy
+- precision
+- recall
+model-index:
+- name: electra-5-epoch-sentiment
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: tweet_eval
+      type: tweet_eval
+      config: sentiment
+      split: test
+      args: sentiment
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.6893520026050146
+    - name: Precision
+      type: precision
+      value: 0.6913776305729754
+    - name: Recall
+      type: recall
+      value: 0.6893520026050146
+---
+
+<!-- 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. -->
+
+# electra-5-epoch-sentiment
+
+This model is a fine-tuned version of [google/electra-small-discriminator](https://huggingface.co/google/electra-small-discriminator) on the tweet_eval dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.7949
+- Accuracy: 0.6894
+- Precision: 0.6914
+- Recall: 0.6894
+- Micro-avg-recall: 0.6894
+- Micro-avg-precision: 0.6894
+
+## 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: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Accuracy | Precision | Recall | Micro-avg-recall | Micro-avg-precision |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:----------------:|:-------------------:|
+| 0.5949        | 1.0   | 2851  | 0.6963          | 0.6926   | 0.6943    | 0.6926 | 0.6926           | 0.6926              |
+| 0.6502        | 2.0   | 5702  | 0.7348          | 0.6911   | 0.6929    | 0.6911 | 0.6911           | 0.6911              |
+| 0.556         | 3.0   | 8553  | 0.7322          | 0.6943   | 0.6952    | 0.6943 | 0.6943           | 0.6943              |
+| 0.4561        | 4.0   | 11404 | 0.7601          | 0.6895   | 0.6916    | 0.6895 | 0.6895           | 0.6895              |
+| 0.471         | 5.0   | 14255 | 0.7949          | 0.6894   | 0.6914    | 0.6894 | 0.6894           | 0.6894              |
+
+
+### Framework versions
+
+- Transformers 4.33.0
+- Pytorch 2.0.0
+- Datasets 2.1.0
+- Tokenizers 0.13.3

training_args.bin

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