update model card README.md

README.md

@@ -0,0 +1,91 @@
+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- consumer-finance-complaints
+metrics:
+- accuracy
+- f1
+- recall
+- precision
+model-index:
+- name: distilroberta-base-wandb-week-3-complaints-classifier-512
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: consumer-finance-complaints
+      type: consumer-finance-complaints
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.8038326283064064
+    - name: F1
+      type: f1
+      value: 0.791857014338201
+    - name: Recall
+      type: recall
+      value: 0.8038326283064064
+    - name: Precision
+      type: precision
+      value: 0.7922430702228043
+---
+
+<!-- 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. -->
+
+# distilroberta-base-wandb-week-3-complaints-classifier-512
+
+This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-base) on the consumer-finance-complaints dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.6004
+- Accuracy: 0.8038
+- F1: 0.7919
+- Recall: 0.8038
+- Precision: 0.7922
+
+## 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: 1.7835312622444155e-05
+- 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_steps: 512
+- num_epochs: 2
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Recall | Precision |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:---------:|
+| 0.7559        | 0.61  | 1500 | 0.7307          | 0.7733   | 0.7411 | 0.7733 | 0.7286    |
+| 0.6361        | 1.22  | 3000 | 0.6559          | 0.7846   | 0.7699 | 0.7846 | 0.7718    |
+| 0.5774        | 1.83  | 4500 | 0.6004          | 0.8038   | 0.7919 | 0.8038 | 0.7922    |
+
+
+### Framework versions
+
+- Transformers 4.20.1
+- Pytorch 1.11.0+cu102
+- Datasets 2.3.2
+- Tokenizers 0.12.1