End of training

README.md

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+---
+license: apache-2.0
+base_model: t5-small
+tags:
+- generated_from_trainer
+metrics:
+- rouge
+- bleu
+model-index:
+- name: Fine_Tuned_T5_small_for_DailyDialog
+  results: []
+---
+
+<!-- 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. -->
+
+# Fine_Tuned_T5_small_for_DailyDialog
+
+This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5891
+- Rouge1: 11.0459
+- Rouge2: 2.2404
+- Rougel: 10.5072
+- Rougelsum: 10.7781
+- Bleu: 0.8903
+- Gen Len: 7.111
+
+## 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: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 10
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2 | Rougel  | Rougelsum | Bleu   | Gen Len |
+|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|:------:|:-------:|
+| 2.0809        | 1.0   | 313  | 1.7698          | 9.3634  | 1.6744 | 8.9437  | 9.0705    | 0.6728 | 8.217   |
+| 1.4771        | 2.0   | 626  | 1.3016          | 10.1104 | 1.7728 | 9.6869  | 9.8809    | 0.0    | 6.527   |
+| 1.2084        | 3.0   | 939  | 1.0781          | 10.3142 | 2.0722 | 9.8421  | 10.0426   | 0.7095 | 6.272   |
+| 1.0171        | 4.0   | 1252 | 0.9219          | 10.299  | 2.107  | 9.8825  | 10.1102   | 0.7598 | 6.246   |
+| 0.9029        | 5.0   | 1565 | 0.7993          | 10.5767 | 2.0701 | 10.0645 | 10.3152   | 0.88   | 6.94    |
+| 0.7979        | 6.0   | 1878 | 0.7169          | 10.618  | 2.0406 | 10.0889 | 10.3652   | 0.9014 | 7.047   |
+| 0.7266        | 7.0   | 2191 | 0.6627          | 10.8584 | 2.1613 | 10.292  | 10.575    | 0.8766 | 6.769   |
+| 0.692         | 8.0   | 2504 | 0.6231          | 11.2891 | 2.2669 | 10.7278 | 11.0423   | 0.9933 | 7.273   |
+| 0.6724        | 9.0   | 2817 | 0.5956          | 11.2029 | 2.2399 | 10.6659 | 10.9419   | 0.9988 | 7.512   |
+| 0.65          | 10.0  | 3130 | 0.5891          | 11.0459 | 2.2404 | 10.5072 | 10.7781   | 0.8903 | 7.111   |
+
+
+### Framework versions
+
+- Transformers 4.32.0
+- Pytorch 2.0.1+cu118
+- Datasets 2.14.4
+- Tokenizers 0.13.3

config.json

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+{
+  "_name_or_path": "t5-small",
+  "architectures": [
+    "T5ForConditionalGeneration"
+  ],
+  "classifier_dropout": 0.0,
+  "d_ff": 2048,
+  "d_kv": 64,
+  "d_model": 512,
+  "decoder_start_token_id": 0,
+  "dense_act_fn": "relu",
+  "dropout_rate": 0.1,
+  "eos_token_id": 1,
+  "feed_forward_proj": "relu",
+  "initializer_factor": 1.0,
+  "is_encoder_decoder": true,
+  "is_gated_act": false,
+  "layer_norm_epsilon": 1e-06,
+  "model_type": "t5",
+  "n_positions": 512,
+  "num_decoder_layers": 6,
+  "num_heads": 8,
+  "num_layers": 6,
+  "output_past": true,
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+  "relative_attention_max_distance": 128,
+  "relative_attention_num_buckets": 32,
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+    },
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+      "early_stopping": true,
+      "max_length": 300,
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+      "prefix": "translate English to German: "
+    },
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+      "prefix": "translate English to French: "
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+      "num_beams": 4,
+      "prefix": "translate English to Romanian: "
+    }
+  },
+  "torch_dtype": "float32",
+  "transformers_version": "4.32.0",
+  "use_cache": true,
+  "vocab_size": 32104
+}

generation_config.json

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+  "transformers_version": "4.32.0"
+}

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