End of training

README.md

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+---
+license: apache-2.0
+base_model: t5-large
+tags:
+- generated_from_trainer
+datasets:
+- super_glue
+metrics:
+- accuracy
+model-index:
+- name: t5-large_boolq_dense_epochs-5
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: super_glue
+      type: super_glue
+      config: boolq
+      split: validation
+      args: boolq
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.846177370030581
+---
+
+<!-- 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. -->
+
+# t5-large_boolq_dense_epochs-5
+
+This model is a fine-tuned version of [t5-large](https://huggingface.co/t5-large) on the super_glue dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3715
+- Accuracy: 0.8462
+
+## 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: 8
+- eval_batch_size: 16
+- seed: 0
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 32
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 20
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.6792        | 0.17  | 50   | 0.6652          | 0.6217   |
+| 0.66          | 0.34  | 100  | 0.6595          | 0.6220   |
+| 0.6614        | 0.51  | 150  | 0.6548          | 0.6232   |
+| 0.636         | 0.68  | 200  | 0.6122          | 0.6985   |
+| 0.4882        | 0.85  | 250  | 0.4702          | 0.7847   |
+| 0.5068        | 1.02  | 300  | 0.4639          | 0.7862   |
+| 0.3332        | 1.19  | 350  | 0.5297          | 0.7908   |
+| 0.4296        | 1.36  | 400  | 0.3955          | 0.8373   |
+| 0.356         | 1.53  | 450  | 0.4013          | 0.8410   |
+| 0.3227        | 1.7   | 500  | 0.3715          | 0.8462   |
+| 0.3516        | 1.87  | 550  | 0.3724          | 0.8428   |
+| 0.2169        | 2.04  | 600  | 0.3906          | 0.8477   |
+| 0.2199        | 2.21  | 650  | 0.4061          | 0.8572   |
+| 0.1969        | 2.37  | 700  | 0.4351          | 0.8550   |
+| 0.2713        | 2.54  | 750  | 0.5411          | 0.8584   |
+| 0.2458        | 2.71  | 800  | 0.3924          | 0.8627   |
+| 0.2134        | 2.88  | 850  | 0.3973          | 0.8630   |
+| 0.1636        | 3.05  | 900  | 0.4933          | 0.8590   |
+| 0.1108        | 3.22  | 950  | 0.9926          | 0.8621   |
+| 0.1433        | 3.39  | 1000 | 0.6679          | 0.8602   |
+
+
+### Framework versions
+
+- Transformers 4.34.1
+- Pytorch 2.1.0+cu118
+- Datasets 2.14.6
+- Tokenizers 0.14.1

pytorch_model.bin

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