End of training

README.md

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+---
+library_name: transformers
+base_model: MingZhong/DialogLED-base-16384
+tags:
+- generated_from_trainer
+metrics:
+- rouge
+model-index:
+- name: LED-note-modified
+  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. -->
+
+# LED-note-modified
+
+This model is a fine-tuned version of [MingZhong/DialogLED-base-16384](https://huggingface.co/MingZhong/DialogLED-base-16384) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4517
+- Rouge1: 0.1441
+- Rouge2: 0.0896
+- Rougel: 0.1067
+
+## 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: 1
+- eval_batch_size: 1
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 2
+- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- num_epochs: 2
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel |
+|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|
+| 0.4719        | 1.0   | 800  | 0.4643          | 0.1437 | 0.0886 | 0.1062 |
+| 0.4267        | 2.0   | 1600 | 0.4517          | 0.1441 | 0.0896 | 0.1067 |
+
+
+### Framework versions
+
+- Transformers 4.51.0
+- Pytorch 2.6.0+cu124
+- Datasets 3.5.0
+- Tokenizers 0.21.1

added_tokens.json

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config.json

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+{
+  "activation_dropout": 0.0,
+  "activation_function": "gelu",
+  "architectures": [
+    "LEDForConditionalGeneration"
+  ],
+  "attention_dropout": 0.0,
+  "attention_window": [
+    1024,
+    1024,
+    1024,
+    1024,
+    1024,
+    1024
+  ],
+  "bos_token_id": 0,
+  "classif_dropout": 0.0,
+  "classifier_dropout": 0.0,
+  "d_model": 768,
+  "decoder_attention_heads": 12,
+  "decoder_ffn_dim": 3072,
+  "decoder_layerdrop": 0.0,
+  "decoder_layers": 6,
+  "decoder_start_token_id": 2,
+  "dropout": 0.1,
+  "early_stopping": null,
+  "encoder_attention_heads": 12,
+  "encoder_ffn_dim": 3072,
+  "encoder_layerdrop": 0.0,
+  "encoder_layers": 6,
+  "eos_token_id": 2,
+  "gradient_checkpointing": false,
+  "id2label": {
+    "0": "LABEL_0",
+    "1": "LABEL_1",
+    "2": "LABEL_2"
+  },
+  "init_std": 0.02,
+  "is_encoder_decoder": true,
+  "label2id": {
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+    "LABEL_1": 1,
+    "LABEL_2": 2
+  },
+  "max_decoder_position_embeddings": 1024,
+  "max_encoder_position_embeddings": 16384,
+  "max_length": null,
+  "min_length": null,
+  "model_type": "led",
+  "no_repeat_ngram_size": null,
+  "num_beams": null,
+  "num_hidden_layers": 6,
+  "pad_token_id": 1,
+  "torch_dtype": "float32",
+  "transformers_version": "4.51.0",
+  "use_cache": true,
+  "vocab_size": 50269
+}

generation_config.json

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+{
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+  "decoder_start_token_id": 2,
+  "early_stopping": true,
+  "eos_token_id": 2,
+  "max_length": 128,
+  "min_length": 64,
+  "no_repeat_ngram_size": 3,
+  "num_beams": 6,
+  "pad_token_id": 1,
+  "transformers_version": "4.51.0"
+}

model.safetensors

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runs/Apr06_14-43-47_40323c26e00d/events.out.tfevents.1743950633.40323c26e00d.706.0

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special_tokens_map.json

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tokenizer_config.json

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+  "tokenizer_class": "LEDTokenizer",
+  "trim_offsets": true,
+  "unk_token": "<unk>"
+}

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