Model save

README.md

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+---
+license: apache-2.0
+base_model: LazarusNLP/IndoNanoT5-base
+tags:
+- generated_from_trainer
+datasets:
+- id_liputan6
+metrics:
+- rouge
+model-index:
+- name: liputan6-seq_bn-rf64
+  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. -->
+
+# liputan6-seq_bn-rf64
+
+This model is a fine-tuned version of [LazarusNLP/IndoNanoT5-base](https://huggingface.co/LazarusNLP/IndoNanoT5-base) on the id_liputan6 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 2.7079
+- Rouge1: 24.9923
+- Rouge2: 10.432
+- Rougel: 21.1505
+- Rougelsum: 22.9477
+- Gen Len: 32.451
+
+## 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: 16
+- eval_batch_size: 32
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 5.0
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
+|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
+| 2.7121        | 1.0   | 63   | 2.7515          | 24.5986 | 10.2547 | 20.7138 | 22.4882   | 33.171  |
+| 2.3483        | 2.0   | 126  | 2.7425          | 25.6586 | 10.7898 | 21.7223 | 23.503    | 33.715  |
+| 2.2546        | 3.0   | 189  | 2.6605          | 24.6676 | 10.1646 | 20.9376 | 22.7405   | 29.451  |
+| 2.1725        | 4.0   | 252  | 2.7043          | 25.3421 | 10.5863 | 21.3692 | 23.2586   | 30.896  |
+| 2.1135        | 5.0   | 315  | 2.7079          | 24.9923 | 10.432  | 21.1505 | 22.9477   | 32.451  |
+
+
+### Framework versions
+
+- Transformers 4.40.2
+- Pytorch 2.3.1+cu121
+- Datasets 2.20.0
+- Tokenizers 0.19.1

adapter-summarization/adapter_config.json

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+    "factorized_phm_W": true,
+    "factorized_phm_rule": false,
+    "hypercomplex_nonlinearity": "glorot-uniform",
+    "init_weights": "bert",
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+    "inv_adapter_reduction_factor": null,
+    "is_parallel": false,
+    "learn_phm": true,
+    "leave_out": [],
+    "ln_after": false,
+    "ln_before": false,
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+    "phm_bias": true,
+    "phm_c_init": "normal",
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+    "phm_init_range": 0.0001,
+    "phm_layer": false,
+    "phm_rank": 1,
+    "reduction_factor": 64,
+    "residual_before_ln": true,
+    "scaling": 1.0,
+    "shared_W_phm": false,
+    "shared_phm_rule": true,
+    "use_gating": false
+  },
+  "config_id": "337ea3bbdc05e9b8",
+  "hidden_size": 768,
+  "model_class": "T5AdapterModel",
+  "model_name": "LazarusNLP/IndoNanoT5-base",
+  "model_type": "t5",
+  "name": "adapter-summarization",
+  "version": "0.2.2"
+}

adapter-summarization/pytorch_adapter.bin

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default/head_config.json

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+  "config": {
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+    "shift_labels": false,
+    "vocab_size": 32128
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+  "hidden_size": 768,
+  "model_class": "T5AdapterModel",
+  "model_name": "LazarusNLP/IndoNanoT5-base",
+  "model_type": "t5",
+  "name": "default",
+  "version": "0.2.2"
+}

default/pytorch_model_head.bin

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