Model save

README.md

@@ -0,0 +1,64 @@
+---
+license: apache-2.0
+base_model: bert-base-uncased
+tags:
+- generated_from_trainer
+datasets:
+- swag
+metrics:
+- accuracy
+model-index:
+- name: bert-base-uncased-finetuned-swag
+  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. -->
+
+# bert-base-uncased-finetuned-swag
+
+This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the swag dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.7187
+- Accuracy: 0.7223
+
+## 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: 32
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.9645        | 1.0   | 2299 | 0.7779          | 0.6998   |
+| 0.8942        | 2.0   | 4598 | 0.7322          | 0.7184   |
+| 0.8907        | 3.0   | 6897 | 0.7187          | 0.7223   |
+
+
+### Framework versions
+
+- Transformers 4.32.1
+- Pytorch 2.1.0
+- Datasets 2.12.0
+- Tokenizers 0.13.3

adapter_model.bin

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:ceee4acb671aff5d46be3de7c9705e58e4f212344aa017374b8af983e0be7fb8
+oid sha256:3115e0ea7fb70278115d0a297165a13d77792f8021af537a107a84a9683b821f
 size 611460