End of training

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README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- samsum
+metrics:
+- rouge
+model-index:
+- name: flan-t5-small-samsum
+  results:
+  - task:
+      name: Sequence-to-sequence Language Modeling
+      type: text2text-generation
+    dataset:
+      name: samsum
+      type: samsum
+      config: samsum
+      split: test
+      args: samsum
+    metrics:
+    - name: Rouge1
+      type: rouge
+      value: 43.7829
+---
+
+<!-- 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. -->
+
+# flan-t5-small-samsum
+
+This model is a fine-tuned version of [google/flan-t5-small](https://huggingface.co/google/flan-t5-small) on the samsum dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.6325
+- Rouge1: 43.7829
+- Rouge2: 19.4994
+- Rougel: 36.5484
+- Rougelsum: 39.9323
+- Gen Len: 16.8730
+
+## 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: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
+|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
+| 1.8137        | 1.0   | 1842 | 1.6636          | 42.6155 | 18.9113 | 35.7997 | 39.046    | 16.7473 |
+| 1.7502        | 2.0   | 3684 | 1.6408          | 43.3833 | 19.1709 | 36.0178 | 39.5973   | 16.8620 |
+| 1.6864        | 3.0   | 5526 | 1.6372          | 43.31   | 19.2269 | 35.9239 | 39.6082   | 16.8559 |
+| 1.6647        | 4.0   | 7368 | 1.6334          | 43.7043 | 19.462  | 36.4417 | 39.8969   | 16.9512 |
+| 1.6391        | 5.0   | 9210 | 1.6325          | 43.7829 | 19.4994 | 36.5484 | 39.9323   | 16.8730 |
+
+
+### Framework versions
+
+- Transformers 4.27.4
+- Pytorch 2.0.0
+- Datasets 2.11.0
+- Tokenizers 0.13.2

config.json

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+  "_name_or_path": "google/flan-t5-small",
+  "architectures": [
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+  ],
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+  "d_kv": 64,
+  "d_model": 512,
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+  "feed_forward_proj": "gated-gelu",
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+  "is_gated_act": true,
+  "layer_norm_epsilon": 1e-06,
+  "model_type": "t5",
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+  "num_heads": 6,
+  "num_layers": 8,
+  "output_past": true,
+  "pad_token_id": 0,
+  "relative_attention_max_distance": 128,
+  "relative_attention_num_buckets": 32,
+  "task_specific_params": {
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+      "length_penalty": 2.0,
+      "max_length": 200,
+      "min_length": 30,
+      "no_repeat_ngram_size": 3,
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+      "prefix": "summarize: "
+    },
+    "translation_en_to_de": {
+      "early_stopping": true,
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+      "num_beams": 4,
+      "prefix": "translate English to German: "
+    },
+    "translation_en_to_fr": {
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+      "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": "4.27.4",
+  "use_cache": true,
+  "vocab_size": 32128
+}

generation_config.json

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