End of training

README.md

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+---
+base_model: nlpie/distil-clinicalbert
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: distil-clinicalbert-medical-text-classification
+  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. -->
+
+# distil-clinicalbert-medical-text-classification
+
+This model is a fine-tuned version of [nlpie/distil-clinicalbert](https://huggingface.co/nlpie/distil-clinicalbert) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.9496
+- Accuracy: 0.226
+- Precision: 0.2021
+- Recall: 0.226
+- F1: 0.2058
+
+## 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: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 500
+- num_epochs: 30
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| 2.5309        | 1.0   | 250  | 2.6137          | 0.339    | 0.1410    | 0.339  | 0.1943 |
+| 2.0359        | 2.0   | 500  | 2.1867          | 0.357    | 0.2377    | 0.357  | 0.2432 |
+| 1.9003        | 3.0   | 750  | 1.9129          | 0.324    | 0.2801    | 0.324  | 0.2882 |
+| 1.5959        | 4.0   | 1000 | 1.8227          | 0.317    | 0.2995    | 0.317  | 0.2904 |
+| 1.3873        | 5.0   | 1250 | 1.8668          | 0.302    | 0.2670    | 0.302  | 0.2740 |
+| 1.3281        | 6.0   | 1500 | 1.8773          | 0.26     | 0.2264    | 0.26   | 0.2358 |
+| 1.3854        | 7.0   | 1750 | 1.9496          | 0.226    | 0.2021    | 0.226  | 0.2058 |
+
+
+### Framework versions
+
+- Transformers 4.39.3
+- Pytorch 2.1.2
+- Datasets 2.18.0
+- Tokenizers 0.15.2

model.safetensors

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