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README.md

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+---
+tags:
+- generated_from_trainer
+datasets:
+- xsum
+metrics:
+- rouge
+model-index:
+- name: small-5-6-t
+  results:
+  - task:
+      name: Summarization
+      type: summarization
+    dataset:
+      name: xsum
+      type: xsum
+      config: default
+      split: validation
+      args: default
+    metrics:
+    - name: Rouge1
+      type: rouge
+      value: 33.1943
+---
+
+<!-- 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. -->
+
+# small-5-6-t
+
+This model is a fine-tuned version of [models/small-5-6](https://huggingface.co/models/small-5-6) on the xsum dataset.
+It achieves the following results on the evaluation set:
+- Loss: 2.0753
+- Rouge1: 33.1943
+- Rouge2: 11.0514
+- Rougel: 26.0966
+- Rougelsum: 26.0978
+- Gen Len: 28.4358
+
+## 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: 32
+- eval_batch_size: 16
+- seed: 42
+- gradient_accumulation_steps: 2
+- 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
+
+### Training results
+
+
+
+### Framework versions
+
+- Transformers 4.27.0.dev0
+- Pytorch 1.12.1+cu113
+- Datasets 2.10.0
+- Tokenizers 0.13.2

all_results.json

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+    "eval_loss": 2.0753448009490967,
+    "eval_rouge1": 33.1943,
+    "eval_rouge2": 11.0514,
+    "eval_rougeL": 26.0966,
+    "eval_rougeLsum": 26.0978,
+    "eval_runtime": 584.408,
+    "eval_samples": 11327,
+    "eval_samples_per_second": 19.382,
+    "eval_steps_per_second": 1.211,
+    "train_loss": 2.2860778256571477,
+    "train_runtime": 9841.2733,
+    "train_samples": 204017,
+    "train_samples_per_second": 62.192,
+    "train_steps_per_second": 0.972
+}

config.json

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+  ],
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+  "relative_attention_max_distance": 128,
+  "relative_attention_num_buckets": 32,
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+      "min_length": 30,
+      "no_repeat_ngram_size": 3,
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+      "prefix": "summarize: "
+    },
+    "translation_en_to_de": {
+      "early_stopping": true,
+      "max_length": 300,
+      "num_beams": 4,
+      "prefix": "translate English to German: "
+    },
+    "translation_en_to_fr": {
+      "early_stopping": true,
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+      "num_beams": 4,
+      "prefix": "translate English to French: "
+    },
+    "translation_en_to_ro": {
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+      "max_length": 300,
+      "num_beams": 4,
+      "prefix": "translate English to Romanian: "
+    }
+  },
+  "tie_word_embeddings": false,
+  "torch_dtype": "float32",
+  "transformers_version": "4.27.0.dev0",
+  "use_cache": true,
+  "vocab_size": 32128
+}

eval_results.json

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+    "eval_rouge1": 33.1943,
+    "eval_rouge2": 11.0514,
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+    "eval_rougeLsum": 26.0978,
+    "eval_runtime": 584.408,
+    "eval_samples": 11327,
+    "eval_samples_per_second": 19.382,
+    "eval_steps_per_second": 1.211
+}

generation_config.json

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+  "transformers_version": "4.27.0.dev0"
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