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README.md

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+---
+tags:
+- generated_from_trainer
+datasets:
+- xsum
+metrics:
+- rouge
+model-index:
+- name: base-2-2-t
+  results:
+  - task:
+      name: Summarization
+      type: summarization
+    dataset:
+      name: xsum
+      type: xsum
+      config: default
+      split: validation
+      args: default
+    metrics:
+    - name: Rouge1
+      type: rouge
+      value: 5.7782
+---
+
+<!-- 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. -->
+
+# base-2-2-t
+
+This model is a fine-tuned version of [x/base-2-2](https://huggingface.co/x/base-2-2) on the xsum dataset.
+It achieves the following results on the evaluation set:
+- Loss: nan
+- Rouge1: 5.7782
+- Rouge2: 0.064
+- Rougel: 5.1661
+- Rougelsum: 5.1836
+- Gen Len: 122.6594
+
+## 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: 2
+- eval_batch_size: 4
+- seed: 42
+- gradient_accumulation_steps: 32
+- 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 0.12.1

all_results.json

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+    "eval_rouge2": 0.064,
+    "eval_rougeL": 5.1661,
+    "eval_rougeLsum": 5.1836,
+    "eval_runtime": 1957.8518,
+    "eval_samples": 11327,
+    "eval_samples_per_second": 5.785,
+    "eval_steps_per_second": 1.446,
+    "train_loss": NaN,
+    "train_runtime": 19100.0105,
+    "train_samples": 204017,
+    "train_samples_per_second": 32.045,
+    "train_steps_per_second": 0.501
+}

config.json

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+  "_name_or_path": "x/base-2-2",
+  "architectures": [
+    "T5ForConditionalGeneration"
+  ],
+  "d_ff": 2048,
+  "d_kv": 64,
+  "d_model": 768,
+  "decoder_start_token_id": 0,
+  "dense_act_fn": "gelu_new",
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+  "eos_token_id": 1,
+  "feed_forward_proj": "gated-gelu",
+  "initializer_factor": 1.0,
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+  "is_gated_act": true,
+  "layer_norm_epsilon": 1e-06,
+  "model_type": "t5",
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+  "num_heads": 12,
+  "num_layers": 4,
+  "output_past": true,
+  "pad_token_id": 0,
+  "relative_attention_max_distance": 128,
+  "relative_attention_num_buckets": 32,
+  "task_specific_params": {
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+      "early_stopping": true,
+      "length_penalty": 2.0,
+      "max_length": 200,
+      "min_length": 30,
+      "no_repeat_ngram_size": 3,
+      "num_beams": 4,
+      "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,
+      "max_length": 300,
+      "num_beams": 4,
+      "prefix": "translate English to French: "
+    },
+    "translation_en_to_ro": {
+      "early_stopping": true,
+      "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_loss": NaN,
+    "eval_rouge1": 5.7782,
+    "eval_rouge2": 0.064,
+    "eval_rougeL": 5.1661,
+    "eval_rougeLsum": 5.1836,
+    "eval_runtime": 1957.8518,
+    "eval_samples": 11327,
+    "eval_samples_per_second": 5.785,
+    "eval_steps_per_second": 1.446
+}

generation_config.json

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+  "eos_token_id": 1,
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+  "transformers_version": "4.27.0.dev0"
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