update model card README.md

README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- consumer-finance-complaints
+metrics:
+- accuracy
+- f1
+- recall
+- precision
+model-index:
+- name: distilbert-base-uncased-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: 0.6745323887671373
+    - name: F1
+      type: f1
+      value: 0.6355967633316707
+    - name: Recall
+      type: recall
+      value: 0.6745323887671373
+    - name: Precision
+      type: precision
+      value: 0.6122130681567332
+---
+
+<!-- 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-wandb-week-3-complaints-classifier-512
+
+This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the consumer-finance-complaints dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.0839
+- Accuracy: 0.6745
+- F1: 0.6356
+- Recall: 0.6745
+- Precision: 0.6122
+
+## 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: 0.0007879237562376572
+- 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:---------:|
+| 1.2707        | 0.61  | 1500 | 1.3009          | 0.6381   | 0.5848 | 0.6381 | 0.5503    |
+| 1.1348        | 1.22  | 3000 | 1.1510          | 0.6610   | 0.6178 | 0.6610 | 0.5909    |
+| 1.0649        | 1.83  | 4500 | 1.0839          | 0.6745   | 0.6356 | 0.6745 | 0.6122    |
+
+
+### Framework versions
+
+- Transformers 4.20.1
+- Pytorch 1.11.0+cu102
+- Datasets 2.3.2
+- Tokenizers 0.12.1