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-bs-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-bs-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: 1.1930
+- Accuracy: 0.5941
+- F1: 0.5907
+- Precision: 0.5913
+- Recall: 0.5941
+
+## 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: 64
+- eval_batch_size: 64
+- 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
+| No log        | 1.0   | 44   | 1.4290          | 0.4439   | 0.3994 | 0.4597    | 0.4439 |
+| 1.5279        | 2.0   | 88   | 1.2962          | 0.5076   | 0.4992 | 0.5300    | 0.5076 |
+| 1.0713        | 3.0   | 132  | 1.2973          | 0.5293   | 0.5328 | 0.5564    | 0.5293 |
+| 0.624         | 4.0   | 176  | 1.3405          | 0.5583   | 0.5550 | 0.5559    | 0.5583 |
+| 0.3372        | 5.0   | 220  | 1.3920          | 0.5424   | 0.5445 | 0.5515    | 0.5424 |
+
+
+### Framework versions
+
+- Transformers 4.31.0
+- Pytorch 2.0.1+cu118
+- Datasets 2.13.1
+- Tokenizers 0.13.3