update model card README.md

README.md

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+---
+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-v6
+  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-v6
+
+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: 1.4919
+- Accuracy: 0.7204
+- F1: 0.7215
+- Precision: 0.7239
+- Recall: 0.7204
+
+## 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
+| 0.9855        | 1.0   | 937  | 1.0026          | 0.6225   | 0.6227 | 0.6604    | 0.6225 |
+| 0.6191        | 2.0   | 1874 | 0.8113          | 0.7090   | 0.7056 | 0.7160    | 0.7090 |
+| 0.2736        | 3.0   | 2811 | 0.9598          | 0.7084   | 0.7070 | 0.7099    | 0.7084 |
+| 0.1399        | 4.0   | 3748 | 1.2784          | 0.7130   | 0.7126 | 0.7151    | 0.7130 |
+| 0.0521        | 5.0   | 4685 | 1.5455          | 0.7152   | 0.7163 | 0.7182    | 0.7152 |
+
+
+### Framework versions
+
+- Transformers 4.31.0
+- Pytorch 2.0.1+cu118
+- Datasets 2.13.1
+- Tokenizers 0.13.3