update model card README.md

README.md

@@ -0,0 +1,71 @@
+---
+license: apache-2.0
+base_model: distilbert-base-uncased
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+- precision
+- recall
+model-index:
+- name: distilbert-base-uncased-english-cefr-lexical-evaluation-dt-v1
+  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-base-uncased-english-cefr-lexical-evaluation-dt-v1
+
+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: 0.5309
+- Accuracy: 0.8716
+- F1: 0.8713
+- Precision: 0.8714
+- Recall: 0.8716
+
+## 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: 0.0001
+- train_batch_size: 32
+- eval_batch_size: 32
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     | Precision | Recall |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
+| 0.6225        | 1.0   | 3403  | 0.6408          | 0.7578   | 0.7538 | 0.7826    | 0.7578 |
+| 0.3645        | 2.0   | 6806  | 0.4180          | 0.8597   | 0.8573 | 0.8554    | 0.8597 |
+| 0.2349        | 3.0   | 10209 | 0.4452          | 0.8631   | 0.8621 | 0.8637    | 0.8631 |
+| 0.1269        | 4.0   | 13612 | 0.5257          | 0.8694   | 0.8690 | 0.8690    | 0.8694 |
+| 0.0605        | 5.0   | 17015 | 0.6865          | 0.8671   | 0.8668 | 0.8669    | 0.8671 |
+
+
+### Framework versions
+
+- Transformers 4.31.0
+- Pytorch 2.0.1+cu118
+- Datasets 2.13.1
+- Tokenizers 0.13.3