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-lr-v2
+  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-lr-v2
+
+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: 1.6545
+- Accuracy: 0.2858
+- F1: 0.1724
+- Precision: 0.1930
+- Recall: 0.2858
+
+## 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: 0.001
+- 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
+| 1.6298        | 1.0   | 87   | 1.6693          | 0.2802   | 0.1665 | 0.1883    | 0.2802 |
+| 1.7023        | 2.0   | 174  | 1.7559          | 0.2194   | 0.1104 | 0.0765    | 0.2194 |
+| 1.732         | 3.0   | 261  | 1.7641          | 0.1731   | 0.0861 | 0.0702    | 0.1731 |
+| 1.7384        | 4.0   | 348  | 1.7511          | 0.2201   | 0.1064 | 0.0776    | 0.2201 |
+| 1.7189        | 5.0   | 435  | 1.7466          | 0.2259   | 0.1101 | 0.0786    | 0.2259 |
+
+
+### Framework versions
+
+- Transformers 4.31.0
+- Pytorch 2.0.1+cu118
+- Datasets 2.13.1
+- Tokenizers 0.13.3