update model card README.md

README.md

@@ -0,0 +1,65 @@
+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+- precision
+- recall
+model-index:
+- name: distilbert-amazon-shoe-reviews-tensorboard
+  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-amazon-shoe-reviews-tensorboard
+
+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: 0.9534
+- Accuracy: 0.5779
+- F1: [0.63189419 0.46645049 0.50381304 0.55843496 0.73060507]
+- Precision: [0.62953754 0.47008547 0.48669202 0.58801498 0.71780957]
+- Recall: [0.63426854 0.46287129 0.52218256 0.53168844 0.74386503]
+
+## 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: 5e-05
+- train_batch_size: 32
+- eval_batch_size: 64
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 1
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1                                                       | Precision                                                | Recall                                                   |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------------------------------------------------------:|:--------------------------------------------------------:|:--------------------------------------------------------:|
+| 0.8776        | 1.0   | 2813 | 0.9534          | 0.5779   | [0.63189419 0.46645049 0.50381304 0.55843496 0.73060507] | [0.62953754 0.47008547 0.48669202 0.58801498 0.71780957] | [0.63426854 0.46287129 0.52218256 0.53168844 0.74386503] |
+
+
+### Framework versions
+
+- Transformers 4.20.1
+- Pytorch 1.12.0+cu102
+- Datasets 2.3.2
+- Tokenizers 0.12.1