update model card README.md

README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+metrics:
+- f1
+- accuracy
+model-index:
+- name: depression_classifier_unweighted_1
+  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. -->
+
+# depression_classifier_unweighted_1
+
+This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.0985
+- F1: {'f1': 0.5363494361475553}
+- Accuracy: {'accuracy': 0.6129429892141757}
+
+## 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: 2e-05
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 6
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | F1                         | Accuracy                         |
+|:-------------:|:-----:|:----:|:---------------:|:--------------------------:|:--------------------------------:|
+| No log        | 1.0   | 451  | 0.7291          | {'f1': 0.5311371197568231} | {'accuracy': 0.6604006163328198} |
+| 0.7994        | 2.0   | 902  | 0.7153          | {'f1': 0.5663643865301549} | {'accuracy': 0.6619414483821263} |
+| 0.6758        | 3.0   | 1353 | 0.7708          | {'f1': 0.5549493182827706} | {'accuracy': 0.6428351309707242} |
+| 0.5489        | 4.0   | 1804 | 0.9657          | {'f1': 0.5398498068923226} | {'accuracy': 0.6061633281972265} |
+| 0.4078        | 5.0   | 2255 | 1.0339          | {'f1': 0.5356239241887982} | {'accuracy': 0.6138674884437596} |
+| 0.3112        | 6.0   | 2706 | 1.0985          | {'f1': 0.5363494361475553} | {'accuracy': 0.6129429892141757} |
+
+
+### Framework versions
+
+- Transformers 4.28.0
+- Pytorch 2.0.1+cu118
+- Datasets 2.12.0
+- Tokenizers 0.13.3