End of training

README.md

@@ -1,4 +1,76 @@
 ---
 license: apache-2.0
-pipeline_tag: zero-shot-classification
----
+base_model: google/electra-small-discriminator
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: electra-small-discriminator-zeroshot-v1.1-none
+  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. -->
+
+# electra-small-discriminator-zeroshot-v1.1-none
+
+This model is a fine-tuned version of [google/electra-small-discriminator](https://huggingface.co/google/electra-small-discriminator) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3747
+- F1 Macro: 0.4125
+- F1 Micro: 0.4620
+- Accuracy Balanced: 0.4701
+- Accuracy: 0.4620
+- Precision Macro: 0.5162
+- Recall Macro: 0.4701
+- Precision Micro: 0.4620
+- Recall Micro: 0.4620
+
+## 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: 80085
+- optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.04
+- num_epochs: 3
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | F1 Macro | F1 Micro | Accuracy Balanced | Accuracy | Precision Macro | Recall Macro | Precision Micro | Recall Micro |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|:--------:|:-----------------:|:--------:|:---------------:|:------------:|:---------------:|:------------:|
+| 0.4765        | 0.32  | 5000  | 0.5300          | 0.7326   | 0.7528   | 0.7329            | 0.7528   | 0.7322          | 0.7329       | 0.7528          | 0.7528       |
+| 0.4408        | 0.65  | 10000 | 0.5099          | 0.7402   | 0.765    | 0.7359            | 0.765    | 0.7463          | 0.7359       | 0.765           | 0.765        |
+| 0.4169        | 0.97  | 15000 | 0.4976          | 0.7473   | 0.7702   | 0.7439            | 0.7702   | 0.7517          | 0.7439       | 0.7702          | 0.7702       |
+| 0.387         | 1.3   | 20000 | 0.4943          | 0.7525   | 0.7742   | 0.7498            | 0.7742   | 0.7559          | 0.7498       | 0.7742          | 0.7742       |
+| 0.3905        | 1.62  | 25000 | 0.4931          | 0.7522   | 0.775    | 0.7484            | 0.775    | 0.7572          | 0.7484       | 0.775           | 0.775        |
+| 0.4001        | 1.95  | 30000 | 0.4924          | 0.7544   | 0.7752   | 0.7524            | 0.7752   | 0.7568          | 0.7524       | 0.7752          | 0.7752       |
+| 0.3995        | 2.27  | 35000 | 0.4900          | 0.7543   | 0.7758   | 0.7517            | 0.7758   | 0.7576          | 0.7517       | 0.7758          | 0.7758       |
+| 0.3981        | 2.6   | 40000 | 0.4906          | 0.7529   | 0.7742   | 0.7504            | 0.7742   | 0.7558          | 0.7504       | 0.7742          | 0.7742       |
+| 0.4232        | 2.92  | 45000 | 0.4904          | 0.7544   | 0.776    | 0.7516            | 0.776    | 0.7579          | 0.7516       | 0.776           | 0.776        |
+
+
+### Framework versions
+
+- Transformers 4.33.3
+- Pytorch 2.1.2+cu121
+- Datasets 2.16.1
+- Tokenizers 0.13.3

model.safetensors

@@ -1,3 +1,3 @@
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 size 27122724