End of training

README.md

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+---
+license: apache-2.0
+base_model: distilbert-base-uncased
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: DistilBERT-finetuned-ner-copious
+  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. -->
+
+# DistilBERT-finetuned-ner-copious
+
+This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0755
+- Precision: 0.6056
+- Recall: 0.6565
+- F1: 0.6300
+- Accuracy: 0.9752
+
+## 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: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 1.0   | 63   | 0.1322          | 0.3129    | 0.2884 | 0.3002 | 0.9529   |
+| No log        | 2.0   | 126  | 0.0842          | 0.5190    | 0.5739 | 0.5451 | 0.9711   |
+| No log        | 3.0   | 189  | 0.0772          | 0.5765    | 0.6174 | 0.5962 | 0.9740   |
+| No log        | 4.0   | 252  | 0.0751          | 0.6035    | 0.6464 | 0.6242 | 0.9751   |
+| No log        | 5.0   | 315  | 0.0755          | 0.6056    | 0.6565 | 0.6300 | 0.9752   |
+
+
+### Framework versions
+
+- Transformers 4.33.2
+- Pytorch 2.0.1+cu118
+- Datasets 2.14.5
+- Tokenizers 0.13.3