Training in progress, step 500

README.md

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+---
+license: apache-2.0
+base_model: Danish-summarisation/DanSumT5-base
+tags:
+- generated_from_trainer
+metrics:
+- rouge
+model-index:
+- name: DanSumT5-base-finetuned-test_6887
+  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. -->
+
+# DanSumT5-base-finetuned-test_6887
+
+This model is a fine-tuned version of [Danish-summarisation/DanSumT5-base](https://huggingface.co/Danish-summarisation/DanSumT5-base) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 2.5277
+- Rouge1: 31.3188
+- Rouge2: 7.8236
+- Rougel: 17.8296
+- Rougelsum: 28.6162
+- Gen Len: 127.0
+
+## 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: 3
+- eval_batch_size: 3
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 12
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 15
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2 | Rougel  | Rougelsum | Gen Len |
+|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
+| No log        | 0.99  | 66   | 2.7401          | 29.9221 | 6.3861 | 16.5877 | 27.0611   | 125.09  |
+| No log        | 1.99  | 133  | 2.6815          | 30.6874 | 6.9413 | 16.9609 | 27.8851   | 125.98  |
+| No log        | 3.0   | 200  | 2.6440          | 31.2045 | 7.4012 | 17.7421 | 28.3497   | 126.63  |
+| No log        | 4.0   | 267  | 2.6199          | 31.3329 | 7.4574 | 17.8549 | 28.643    | 126.98  |
+| No log        | 4.99  | 333  | 2.5984          | 31.5184 | 7.7763 | 17.9153 | 29.0627   | 127.0   |
+| No log        | 5.99  | 400  | 2.5822          | 31.8839 | 7.9755 | 18.0572 | 29.2282   | 126.65  |
+| No log        | 7.0   | 467  | 2.5677          | 31.5939 | 7.9515 | 17.865  | 29.2019   | 126.45  |
+| 2.8684        | 8.0   | 534  | 2.5587          | 31.4931 | 7.6042 | 17.6853 | 28.8366   | 126.79  |
+| 2.8684        | 8.99  | 600  | 2.5496          | 31.105  | 7.6714 | 17.5128 | 28.5242   | 126.78  |
+| 2.8684        | 9.99  | 667  | 2.5423          | 31.6087 | 8.0358 | 17.9956 | 28.9514   | 126.78  |
+| 2.8684        | 11.0  | 734  | 2.5364          | 31.411  | 7.9534 | 17.895  | 28.7595   | 127.0   |
+| 2.8684        | 12.0  | 801  | 2.5326          | 31.4648 | 7.9777 | 17.9589 | 28.8168   | 127.0   |
+| 2.8684        | 12.99 | 867  | 2.5296          | 31.374  | 7.8341 | 17.8341 | 28.8146   | 127.0   |
+| 2.8684        | 13.99 | 934  | 2.5278          | 31.2822 | 7.7789 | 17.7983 | 28.5903   | 127.0   |
+| 2.8684        | 14.83 | 990  | 2.5277          | 31.3188 | 7.8236 | 17.8296 | 28.6162   | 127.0   |
+
+
+### Framework versions
+
+- Transformers 4.32.1
+- Pytorch 2.1.0
+- Datasets 2.12.0
+- Tokenizers 0.13.3

config.json

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+{
+  "_name_or_path": "Danish-summarisation/DanSumT5-base",
+  "architectures": [
+    "MT5ForConditionalGeneration"
+  ],
+  "classifier_dropout": 0.0,
+  "d_ff": 2048,
+  "d_kv": 64,
+  "d_model": 768,
+  "decoder_start_token_id": 0,
+  "dense_act_fn": "gelu_new",
+  "dropout_rate": 0.1,
+  "eos_token_id": 1,
+  "feed_forward_proj": "gated-gelu",
+  "initializer_factor": 1.0,
+  "is_encoder_decoder": true,
+  "is_gated_act": true,
+  "layer_norm_epsilon": 1e-06,
+  "length_penalty": 5.0,
+  "max_length": 128,
+  "min_length": 9,
+  "model_type": "mt5",
+  "no_repeat_ngram_size": 3,
+  "num_beams": 2,
+  "num_decoder_layers": 12,
+  "num_heads": 12,
+  "num_layers": 12,
+  "output_past": true,
+  "pad_token_id": 0,
+  "relative_attention_max_distance": 128,
+  "relative_attention_num_buckets": 32,
+  "tie_word_embeddings": false,
+  "tokenizer_class": "T5Tokenizer",
+  "torch_dtype": "float32",
+  "transformers_version": "4.32.1",
+  "use_cache": true,
+  "vocab_size": 250112
+}

generation_config.json

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+{
+  "decoder_start_token_id": 0,
+  "eos_token_id": 1,
+  "length_penalty": 5.0,
+  "max_length": 128,
+  "min_length": 9,
+  "no_repeat_ngram_size": 3,
+  "num_beams": 2,
+  "pad_token_id": 0,
+  "transformers_version": "4.32.1"
+}

pytorch_model.bin

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special_tokens_map.json

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+  "pad_token": "<pad>",
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+}

spiece.model

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tokenizer_config.json

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+  "clean_up_tokenization_spaces": true,
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+  "legacy": true,
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+}

training_args.bin

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