End of training

README.md

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+---
+library_name: peft
+license: apache-2.0
+base_model: muchad/idt5-base
+tags:
+- generated_from_trainer
+metrics:
+- rouge
+- bleu
+model-index:
+- name: idt5-base-ae_adapter_v2
+  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. -->
+
+# idt5-base-ae_adapter_v2
+
+This model is a fine-tuned version of [muchad/idt5-base](https://huggingface.co/muchad/idt5-base) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.1193
+- Rouge1: 0.3286
+- Rouge2: 0.1753
+- Rougel: 0.3016
+- Rougelsum: 0.3039
+- Bleu: 0.1368
+
+## 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: 0.0001
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Use 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: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Bleu   |
+|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:------:|
+| 1.4796        | 1.0   | 1695 | 1.2868          | 0.2748 | 0.1159 | 0.2489 | 0.2521    | 0.1543 |
+| 1.2884        | 2.0   | 3390 | 1.1966          | 0.3005 | 0.1461 | 0.2733 | 0.2760    | 0.1235 |
+| 1.1838        | 3.0   | 5085 | 1.1449          | 0.3188 | 0.1644 | 0.2914 | 0.2938    | 0.1319 |
+| 1.152         | 4.0   | 6780 | 1.1288          | 0.3266 | 0.1738 | 0.2997 | 0.3018    | 0.1364 |
+| 1.1397        | 5.0   | 8475 | 1.1193          | 0.3286 | 0.1753 | 0.3016 | 0.3039    | 0.1368 |
+
+
+### Framework versions
+
+- PEFT 0.13.2
+- Transformers 4.46.0
+- Pytorch 2.4.0a0+f70bd71a48.nv24.06
+- Datasets 3.0.2
+- Tokenizers 0.20.1

adapter_config.json

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+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "muchad/idt5-base",
+  "bias": "none",
+  "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": 16,
+  "lora_dropout": 0.05,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 64,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "v",
+    "q"
+  ],
+  "task_type": "SEQ_2_SEQ_LM",
+  "use_dora": false,
+  "use_rslora": false
+}

adapter_model.safetensors

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+size 28331904

special_tokens_map.json

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+{
+  "eos_token": {
+    "content": "</s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": {
+    "content": "<pad>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "unk_token": {
+    "content": "<unk>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

spiece.model

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tokenizer_config.json

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+{
+  "add_prefix_space": true,
+  "added_tokens_decoder": {
+    "0": {
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+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
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+    "1": {
+      "content": "</s>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
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+      "lstrip": false,
+      "normalized": false,
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+      "single_word": false,
+      "special": true
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+  },
+  "additional_special_tokens": [],
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "</s>",
+  "extra_ids": 0,
+  "legacy": true,
+  "model_max_length": 1000000000000000019884624838656,
+  "pad_token": "<pad>",
+  "sp_model_kwargs": {},
+  "tokenizer_class": "T5Tokenizer",
+  "unk_token": "<unk>"
+}

training_args.bin

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