End of training

README.md

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+---
+library_name: peft
+license: apache-2.0
+base_model: allenai/led-base-16384
+tags:
+- generated_from_trainer
+metrics:
+- rouge
+- bleu
+- precision
+- recall
+- f1
+model-index:
+- name: Lora_LED_sum_outcome
+  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. -->
+
+# Lora_LED_sum_outcome
+
+This model is a fine-tuned version of [allenai/led-base-16384](https://huggingface.co/allenai/led-base-16384) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 3.7163
+- Rouge1: 0.3771
+- Rouge2: 0.1486
+- Rougel: 0.3048
+- Rougelsum: 0.3041
+- Gen Len: 26.78
+- Bleu: 0.0676
+- Precisions: 0.145
+- Brevity Penalty: 0.7751
+- Length Ratio: 0.7969
+- Translation Length: 934.0
+- Reference Length: 1172.0
+- Precision: 0.8956
+- Recall: 0.8849
+- F1: 0.8901
+- Hashcode: roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.1)
+
+## 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: 0.001
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- 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: 10
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | Bleu   | Precisions | Brevity Penalty | Length Ratio | Translation Length | Reference Length | Precision | Recall | F1     | Hashcode                                                  |
+|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|:------:|:----------:|:---------------:|:------------:|:------------------:|:----------------:|:---------:|:------:|:------:|:---------------------------------------------------------:|
+| 8.5991        | 1.0   | 13   | 6.3567          | 0.296  | 0.0973 | 0.2568 | 0.2557    | 31.66   | 0.0456 | 0.0891     | 1.0             | 1.0751       | 1260.0             | 1172.0           | 0.8683    | 0.8666 | 0.8674 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.1) |
+| 5.6132        | 2.0   | 26   | 4.4329          | 0.3194 | 0.1255 | 0.2695 | 0.2708    | 27.78   | 0.0667 | 0.1161     | 0.9275          | 0.93         | 1090.0             | 1172.0           | 0.8859    | 0.8748 | 0.8802 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.1) |
+| 4.4029        | 3.0   | 39   | 3.8761          | 0.3541 | 0.147  | 0.2867 | 0.2869    | 26.3    | 0.0667 | 0.1404     | 0.7466          | 0.7739       | 907.0              | 1172.0           | 0.8938    | 0.8809 | 0.8871 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.1) |
+| 4.0321        | 4.0   | 52   | 3.7464          | 0.3456 | 0.1434 | 0.2907 | 0.2907    | 23.88   | 0.0623 | 0.1454     | 0.6813          | 0.7227       | 847.0              | 1172.0           | 0.897     | 0.8791 | 0.8878 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.1) |
+| 3.8606        | 5.0   | 65   | 3.7107          | 0.377  | 0.1448 | 0.2955 | 0.2954    | 28.08   | 0.0704 | 0.133      | 0.8931          | 0.8985       | 1053.0             | 1172.0           | 0.8909    | 0.8825 | 0.8866 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.1) |
+| 3.7497        | 6.0   | 78   | 3.7107          | 0.4101 | 0.177  | 0.3294 | 0.3289    | 26.58   | 0.0952 | 0.1707     | 0.7947          | 0.8131       | 953.0              | 1172.0           | 0.9017    | 0.8886 | 0.895  | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.1) |
+| 3.6478        | 7.0   | 91   | 3.7065          | 0.3755 | 0.1524 | 0.3027 | 0.3025    | 27.6    | 0.0654 | 0.1417     | 0.81            | 0.8259       | 968.0              | 1172.0           | 0.8893    | 0.8847 | 0.8869 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.1) |
+| 3.5904        | 8.0   | 104  | 3.7081          | 0.3692 | 0.1483 | 0.3055 | 0.3046    | 27.86   | 0.0669 | 0.1372     | 0.8311          | 0.8439       | 989.0              | 1172.0           | 0.8911    | 0.8834 | 0.8871 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.1) |
+| 3.5673        | 9.0   | 117  | 3.7045          | 0.3724 | 0.1591 | 0.3096 | 0.3081    | 26.8    | 0.0701 | 0.1492     | 0.7667          | 0.7901       | 926.0              | 1172.0           | 0.8958    | 0.8851 | 0.8903 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.1) |
+| 3.5516        | 10.0  | 130  | 3.7163          | 0.3771 | 0.1486 | 0.3048 | 0.3041    | 26.78   | 0.0676 | 0.145      | 0.7751          | 0.7969       | 934.0              | 1172.0           | 0.8956    | 0.8849 | 0.8901 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.1) |
+
+
+### Framework versions
+
+- PEFT 0.15.2
+- Transformers 4.53.1
+- Pytorch 2.7.0+cu126
+- Datasets 3.6.0
+- Tokenizers 0.21.1

adapter_config.json

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+  "base_model_name_or_path": "allenai/led-base-16384",
+  "bias": "none",
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+  "eva_config": null,
+  "exclude_modules": null,
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 32,
+  "lora_bias": false,
+  "lora_dropout": 0.1,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 8,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
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+    "v_proj",
+    "q_proj",
+    "out_proj"
+  ],
+  "task_type": "SEQ_2_SEQ_LM",
+  "trainable_token_indices": null,
+  "use_dora": false,
+  "use_rslora": false
+}

adapter_model.safetensors

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special_tokens_map.json

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tokenizer_config.json

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+{
+  "add_prefix_space": false,
+  "added_tokens_decoder": {
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+}

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