End of training

README.md

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+---
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- accuracy
+- f1
+model-index:
+- name: electricidad-base-ft-diagTrast
+  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. -->
+
+# electricidad-base-ft-diagTrast
+
+This model is a fine-tuned version of [mrm8488/electricidad-base-discriminator](https://huggingface.co/mrm8488/electricidad-base-discriminator) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2111
+- Precision: 0.9653
+- Recall: 0.9627
+- Accuracy: 0.9627
+- F1: 0.9622
+
+## 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: 8
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | Accuracy | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:--------:|:------:|
+| No log        | 1.0   | 150  | 0.9281          | 0.7399    | 0.6567 | 0.6567   | 0.5989 |
+| No log        | 2.0   | 300  | 0.4736          | 0.8680    | 0.8582 | 0.8582   | 0.8581 |
+| No log        | 3.0   | 450  | 0.2584          | 0.9215    | 0.9104 | 0.9104   | 0.9110 |
+| 0.6826        | 4.0   | 600  | 0.3336          | 0.9190    | 0.9104 | 0.9104   | 0.9036 |
+| 0.6826        | 5.0   | 750  | 0.2194          | 0.9458    | 0.9403 | 0.9403   | 0.9398 |
+| 0.6826        | 6.0   | 900  | 0.1984          | 0.9451    | 0.9403 | 0.9403   | 0.9397 |
+| 0.0262        | 7.0   | 1050 | 0.2012          | 0.9582    | 0.9552 | 0.9552   | 0.9552 |
+| 0.0262        | 8.0   | 1200 | 0.2272          | 0.9366    | 0.9328 | 0.9328   | 0.9319 |
+| 0.0262        | 9.0   | 1350 | 0.2111          | 0.9653    | 0.9627 | 0.9627   | 0.9622 |
+| 0.0044        | 10.0  | 1500 | 0.2156          | 0.9587    | 0.9552 | 0.9552   | 0.9543 |
+
+
+### Framework versions
+
+- Transformers 4.27.4
+- Pytorch 2.0.0+cu118
+- Datasets 2.11.0
+- Tokenizers 0.13.3

runs/Apr05_18-27-04_794e70132416/events.out.tfevents.1680719239.794e70132416.24707.0

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runs/Apr05_18-27-04_794e70132416/events.out.tfevents.1680719398.794e70132416.24707.2

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