Training complete

README.md

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+---
+base_model: nghuyong/ernie-2.0-base-en
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: ernie-2.0-base-en
+  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. -->
+
+# ernie-2.0-base-en
+
+This model is a fine-tuned version of [nghuyong/ernie-2.0-base-en](https://huggingface.co/nghuyong/ernie-2.0-base-en) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2022
+- Precision: 0.7745
+- Recall: 0.8255
+- F1: 0.7992
+- Accuracy: 0.9392
+
+## 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: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.2221        | 1.0   | 2078 | 0.2066          | 0.7130    | 0.8024 | 0.7551 | 0.9309   |
+| 0.1813        | 2.0   | 4156 | 0.1972          | 0.7573    | 0.8224 | 0.7885 | 0.9362   |
+| 0.1397        | 3.0   | 6234 | 0.2022          | 0.7745    | 0.8255 | 0.7992 | 0.9392   |
+
+
+### Framework versions
+
+- Transformers 4.35.2
+- Pytorch 2.1.0+cu121
+- Datasets 2.16.1
+- Tokenizers 0.15.1