End of training

README.md

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+---
+library_name: transformers
+base_model: google/pegasus-large
+tags:
+- generated_from_trainer
+model-index:
+- name: pegasus_decomposition
+  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. -->
+
+# pegasus_decomposition
+
+This model is a fine-tuned version of [google/pegasus-large](https://huggingface.co/google/pegasus-large) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: nan
+
+## 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
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss |
+|:-------------:|:-----:|:----:|:---------------:|
+| 0.0           | 1.0   | 3307 | nan             |
+| 0.0           | 2.0   | 6614 | nan             |
+| 0.0           | 3.0   | 9921 | nan             |
+
+
+### Framework versions
+
+- Transformers 4.44.2
+- Pytorch 2.4.1+cu121
+- Datasets 3.0.1
+- Tokenizers 0.19.1

config.json

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+{
+  "_name_or_path": "google/pegasus-large",
+  "activation_dropout": 0.1,
+  "activation_function": "relu",
+  "add_bias_logits": false,
+  "add_final_layer_norm": true,
+  "architectures": [
+    "PegasusForConditionalGeneration"
+  ],
+  "attention_dropout": 0.1,
+  "bos_token_id": 0,
+  "classif_dropout": 0.0,
+  "classifier_dropout": 0.0,
+  "d_model": 1024,
+  "decoder_attention_heads": 16,
+  "decoder_ffn_dim": 4096,
+  "decoder_layerdrop": 0.0,
+  "decoder_layers": 16,
+  "decoder_start_token_id": 0,
+  "dropout": 0.1,
+  "encoder_attention_heads": 16,
+  "encoder_ffn_dim": 4096,
+  "encoder_layerdrop": 0.0,
+  "encoder_layers": 16,
+  "eos_token_id": 1,
+  "extra_pos_embeddings": 1,
+  "force_bos_token_to_be_generated": false,
+  "forced_eos_token_id": 1,
+  "gradient_checkpointing": false,
+  "id2label": {
+    "0": "LABEL_0",
+    "1": "LABEL_1",
+    "2": "LABEL_2"
+  },
+  "init_std": 0.02,
+  "is_encoder_decoder": true,
+  "label2id": {
+    "LABEL_0": 0,
+    "LABEL_1": 1,
+    "LABEL_2": 2
+  },
+  "length_penalty": 0.8,
+  "max_length": 256,
+  "max_position_embeddings": 1024,
+  "model_type": "pegasus",
+  "normalize_before": true,
+  "normalize_embedding": false,
+  "num_beams": 8,
+  "num_hidden_layers": 16,
+  "pad_token_id": 0,
+  "scale_embedding": true,
+  "static_position_embeddings": true,
+  "task_specific_params": {
+    "summarization_aeslc": {
+      "length_penalty": 0.6,
+      "max_length": 32,
+      "max_position_embeddings": 512
+    },
+    "summarization_arxiv": {
+      "length_penalty": 0.8,
+      "max_length": 256,
+      "max_position_embeddings": 1024
+    },
+    "summarization_big_patent": {
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+      "max_length": 256,
+      "max_position_embeddings": 1024
+    },
+    "summarization_billsum": {
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+      "max_length": 256,
+      "max_position_embeddings": 1024
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+    "summarization_cnn_dailymail": {
+      "length_penalty": 0.8,
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+      "max_position_embeddings": 1024
+    },
+    "summarization_gigaword": {
+      "length_penalty": 0.6,
+      "max_length": 32,
+      "max_position_embeddings": 128
+    },
+    "summarization_large": {
+      "length_penalty": 0.8,
+      "max_length": 256,
+      "max_position_embeddings": 1024
+    },
+    "summarization_multi_news": {
+      "length_penalty": 0.8,
+      "max_length": 256,
+      "max_position_embeddings": 1024
+    },
+    "summarization_newsroom": {
+      "length_penalty": 0.8,
+      "max_length": 128,
+      "max_position_embeddings": 512
+    },
+    "summarization_pubmed": {
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+      "max_length": 256,
+      "max_position_embeddings": 1024
+    },
+    "summarization_reddit_tifu": {
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+      "max_position_embeddings": 512
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+    "summarization_wikihow": {
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+      "max_length": 256,
+      "max_position_embeddings": 512
+    },
+    "summarization_xsum": {
+      "length_penalty": 0.8,
+      "max_length": 64,
+      "max_position_embeddings": 512
+    }
+  },
+  "torch_dtype": "float16",
+  "transformers_version": "4.44.2",
+  "use_cache": true,
+  "vocab_size": 96103
+}

generation_config.json

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+{
+  "_from_model_config": true,
+  "bos_token_id": 0,
+  "decoder_start_token_id": 0,
+  "eos_token_id": 1,
+  "forced_eos_token_id": 1,
+  "length_penalty": 0.8,
+  "max_length": 256,
+  "num_beams": 8,
+  "pad_token_id": 0,
+  "transformers_version": "4.44.2"
+}

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training_args.bin

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