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-256
+  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: 0.8234544620559604
+    - name: F1
+      type: f1
+      value: 0.8176243580045963
+    - name: Recall
+      type: recall
+      value: 0.8234544620559604
+    - name: Precision
+      type: precision
+      value: 0.8171438106054644
+---
+
+<!-- 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-256
+
+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: 0.5453
+- Accuracy: 0.8235
+- F1: 0.8176
+- Recall: 0.8235
+- Precision: 0.8171
+
+## 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: 4.097565552226687e-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: 256
+- num_epochs: 2
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Recall | Precision |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:---------:|
+| 0.6691        | 0.61  | 1500 | 0.6475          | 0.7962   | 0.7818 | 0.7962 | 0.7875    |
+| 0.5361        | 1.22  | 3000 | 0.5794          | 0.8161   | 0.8080 | 0.8161 | 0.8112    |
+| 0.4659        | 1.83  | 4500 | 0.5453          | 0.8235   | 0.8176 | 0.8235 | 0.8171    |
+
+
+### Framework versions
+
+- Transformers 4.20.1
+- Pytorch 1.11.0+cu102
+- Datasets 2.3.2
+- Tokenizers 0.12.1