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-v5
+  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-v5
+
+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: 1.6329
+- Accuracy: 0.6599
+- F1: 0.6615
+- Precision: 0.6649
+- Recall: 0.6599
+
+## 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
+| 1.1732        | 1.0   | 367  | 1.0065          | 0.6292   | 0.6249 | 0.6360    | 0.6292 |
+| 0.7751        | 2.0   | 734  | 0.9342          | 0.6649   | 0.6630 | 0.6629    | 0.6649 |
+| 0.3269        | 3.0   | 1101 | 1.1524          | 0.6483   | 0.6491 | 0.6634    | 0.6483 |
+| 0.1226        | 4.0   | 1468 | 1.4517          | 0.6558   | 0.6573 | 0.6594    | 0.6558 |
+| 0.0599        | 5.0   | 1835 | 1.6189          | 0.6697   | 0.6715 | 0.6753    | 0.6697 |
+
+
+### Framework versions
+
+- Transformers 4.31.0
+- Pytorch 2.0.1+cu118
+- Datasets 2.13.1
+- Tokenizers 0.13.3