Training complete

README.md

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+---
+base_model: allenai/scibert_scivocab_cased
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: scibert-finetuned-ner
+  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. -->
+
+# scibert-finetuned-ner
+
+This model is a fine-tuned version of [allenai/scibert_scivocab_cased](https://huggingface.co/allenai/scibert_scivocab_cased) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5054
+- Precision: 0.6
+- Recall: 0.2
+- F1: 0.3
+- Accuracy: 0.8858
+
+## 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: 8
+- 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 | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 1.0   | 7    | 0.7330          | 0.0       | 0.0    | 0.0    | 0.8696   |
+| No log        | 2.0   | 14   | 0.7286          | 0.0       | 0.0    | 0.0    | 0.8696   |
+| No log        | 3.0   | 21   | 0.6185          | 0.0       | 0.0    | 0.0    | 0.8696   |
+| No log        | 4.0   | 28   | 0.5975          | 0.0       | 0.0    | 0.0    | 0.8696   |
+| No log        | 5.0   | 35   | 0.5554          | 0.4444    | 0.0889 | 0.1481 | 0.8777   |
+| No log        | 6.0   | 42   | 0.5463          | 0.3125    | 0.1111 | 0.1639 | 0.8813   |
+| No log        | 7.0   | 49   | 0.5278          | 0.4       | 0.1333 | 0.2    | 0.8831   |
+| No log        | 8.0   | 56   | 0.5277          | 0.4667    | 0.1556 | 0.2333 | 0.8840   |
+| No log        | 9.0   | 63   | 0.5102          | 0.6       | 0.2    | 0.3    | 0.8858   |
+| No log        | 10.0  | 70   | 0.5054          | 0.6       | 0.2    | 0.3    | 0.8858   |
+
+
+### Framework versions
+
+- Transformers 4.34.1
+- Pytorch 2.1.0+cu118
+- Datasets 2.14.6
+- Tokenizers 0.14.1