End of training

README.md

@@ -0,0 +1,70 @@
+---
+license: mit
+base_model: roberta-base
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: roberta-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. -->
+
+# roberta-ner
+
+This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1963
+- Precision: 0.3814
+- Recall: 0.4134
+- F1: 0.3968
+- Accuracy: 0.9525
+
+## 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: 16
+- eval_batch_size: 16
+- 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   | 60   | 0.2553          | 0.1878    | 0.1075 | 0.1368 | 0.9435   |
+| No log        | 2.0   | 120  | 0.2114          | 0.3456    | 0.2235 | 0.2714 | 0.9492   |
+| No log        | 3.0   | 180  | 0.2007          | 0.3372    | 0.3673 | 0.3516 | 0.9494   |
+| No log        | 4.0   | 240  | 0.1976          | 0.3618    | 0.3911 | 0.3758 | 0.9517   |
+| No log        | 5.0   | 300  | 0.1963          | 0.3814    | 0.4134 | 0.3968 | 0.9525   |
+
+
+### Framework versions
+
+- Transformers 4.34.1
+- Pytorch 2.1.0+cu118
+- Datasets 2.14.6
+- Tokenizers 0.14.1