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README.md

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+---
+tags:
+- generated_from_trainer
+datasets:
+- cnn_dailymail
+metrics:
+- rouge
+model-index:
+- name: large-1-6-t
+  results:
+  - task:
+      name: Summarization
+      type: summarization
+    dataset:
+      name: cnn_dailymail 3.0.0
+      type: cnn_dailymail
+      config: 3.0.0
+      split: validation
+      args: 3.0.0
+    metrics:
+    - name: Rouge1
+      type: rouge
+      value: 41.0689
+---
+
+<!-- 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. -->
+
+# large-1-6-t
+
+This model is a fine-tuned version of [cnn/large-1-6/](https://huggingface.co/cnn/large-1-6/) on the cnn_dailymail 3.0.0 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.3957
+- Rouge1: 41.0689
+- Rouge2: 18.5801
+- Rougel: 28.7468
+- Rougelsum: 38.2183
+- Gen Len: 74.2018
+
+## 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: 0.0001
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 64
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: constant
+- num_epochs: 3.0
+- mixed_precision_training: Native AMP
+
+### Training results
+
+
+
+### Framework versions
+
+- Transformers 4.27.0.dev0
+- Pytorch 1.13.0+cu117
+- Datasets 2.7.1
+- Tokenizers 0.13.2

all_results.json

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+    "train_steps_per_second": 0.467
+}

config.json

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+  "torch_dtype": "float32",
+  "transformers_version": "4.27.0.dev0",
+  "use_cache": true,
+  "vocab_size": 32128
+}

eval_results.json

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+}

generation_config.json

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