End of training

README.md

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+---
+license: apache-2.0
+base_model: t5-small
+tags:
+- generated_from_trainer
+datasets:
+- multi_news
+model-index:
+- name: t5-small_multinews_model
+  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. -->
+
+# t5-small_multinews_model
+
+This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the multi_news dataset.
+It achieves the following results on the evaluation set:
+- Loss: 2.6269
+- Rouge Rouge1: 0.1471
+- Rouge Rouge2: 0.0483
+- Rouge Rougel: 0.1131
+- Rouge Rougelsum: 0.1131
+- Bleu Bleu: 0.0003
+- Bleu Precisions: [0.5848502090652357, 0.18492208339182928, 0.08486295668446923, 0.04842115016777968]
+- Bleu Brevity Penalty: 0.0022
+- Bleu Length Ratio: 0.1408
+- Bleu Translation Length: 191567
+- Bleu Reference Length: 1360656
+
+## 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: 2e-05
+- train_batch_size: 4
+- eval_batch_size: 4
+- 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 | Rouge Rouge1 | Rouge Rouge2 | Rouge Rougel | Rouge Rougelsum | Bleu Bleu | Bleu Precisions                                                                     | Bleu Brevity Penalty | Bleu Length Ratio | Bleu Translation Length | Bleu Reference Length |
+|:-------------:|:-----:|:-----:|:---------------:|:------------:|:------------:|:------------:|:---------------:|:---------:|:-----------------------------------------------------------------------------------:|:--------------------:|:-----------------:|:-----------------------:|:---------------------:|
+| 2.9189        | 1.0   | 7870  | 2.6869          | 0.1448       | 0.0474       | 0.1117       | 0.1117          | 0.0003    | [0.5827522821123012, 0.1820493433028088, 0.08242051182628926, 0.04574874477953644]  | 0.0023               | 0.1411            | 192037                  | 1360656               |
+| 2.8435        | 2.0   | 15740 | 2.6535          | 0.1460       | 0.0474       | 0.1122       | 0.1122          | 0.0003    | [0.5809636959568958, 0.18126278620071182, 0.08254004826406995, 0.04636911719064694] | 0.0023               | 0.1410            | 191907                  | 1360656               |
+| 2.7922        | 3.0   | 23610 | 2.6389          | 0.1461       | 0.0477       | 0.1124       | 0.1124          | 0.0003    | [0.581669805398619, 0.18257649098318213, 0.08343485040444401, 0.0471782007379682]   | 0.0022               | 0.1405            | 191160                  | 1360656               |
+| 2.814         | 4.0   | 31480 | 2.6280          | 0.1468       | 0.0478       | 0.1129       | 0.1129          | 0.0003    | [0.5844809737428239, 0.18360803285143726, 0.08381524001996615, 0.04753093788548009] | 0.0022               | 0.1406            | 191262                  | 1360656               |
+| 2.7869        | 5.0   | 39350 | 2.6269          | 0.1471       | 0.0483       | 0.1131       | 0.1131          | 0.0003    | [0.5848502090652357, 0.18492208339182928, 0.08486295668446923, 0.04842115016777968] | 0.0022               | 0.1408            | 191567                  | 1360656               |
+
+
+### Framework versions
+
+- Transformers 4.32.1
+- Pytorch 2.0.1+cu118
+- Datasets 2.14.4
+- Tokenizers 0.13.3

generation_config.json

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+{
+  "decoder_start_token_id": 0,
+  "eos_token_id": 1,
+  "pad_token_id": 0,
+  "transformers_version": "4.32.1"
+}