Model save

README.md

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+---
+license: apache-2.0
+base_model: LazarusNLP/IndoNanoT5-base
+tags:
+- generated_from_trainer
+metrics:
+- rouge
+model-index:
+- name: indosum-seq_bn-rf64-0
+  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. -->
+
+# indosum-seq_bn-rf64-0
+
+This model is a fine-tuned version of [LazarusNLP/IndoNanoT5-base](https://huggingface.co/LazarusNLP/IndoNanoT5-base) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5046
+- Rouge1: 72.0617
+- Rouge2: 64.9137
+- Rougel: 69.0991
+- Rougelsum: 71.1205
+- Gen Len: 102.5733
+
+## 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  |
+|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:--------:|
+| 0.8386        | 1.0   | 892  | 0.5658          | 68.0586 | 60.6185 | 65.0879 | 67.0846   | 102.556  |
+| 0.646         | 2.0   | 1784 | 0.5346          | 69.6096 | 62.3885 | 66.6327 | 68.7343   | 107.088  |
+| 0.6031        | 3.0   | 2676 | 0.5019          | 70.498  | 63.0668 | 67.3204 | 69.5075   | 101.6693 |
+| 0.5753        | 4.0   | 3568 | 0.5093          | 71.6759 | 64.4776 | 68.7095 | 70.7692   | 104.52   |
+| 0.5551        | 5.0   | 4460 | 0.5046          | 72.0617 | 64.9137 | 69.0991 | 71.1205   | 102.5733 |
+
+
+### 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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+{
+  "config": {
+    "adapter_residual_before_ln": false,
+    "cross_adapter": false,
+    "dropout": 0.0,
+    "factorized_phm_W": true,
+    "factorized_phm_rule": false,
+    "hypercomplex_nonlinearity": "glorot-uniform",
+    "init_weights": "bert",
+    "inv_adapter": null,
+    "inv_adapter_reduction_factor": null,
+    "is_parallel": false,
+    "learn_phm": true,
+    "leave_out": [],
+    "ln_after": false,
+    "ln_before": false,
+    "mh_adapter": false,
+    "non_linearity": "relu",
+    "original_ln_after": true,
+    "original_ln_before": true,
+    "output_adapter": true,
+    "phm_bias": true,
+    "phm_c_init": "normal",
+    "phm_dim": 4,
+    "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": {
+    "activation_function": null,
+    "bias": false,
+    "head_type": "seq2seq_lm",
+    "label2id": null,
+    "layer_norm": false,
+    "layers": 1,
+    "shift_labels": false,
+    "vocab_size": 32128
+  },
+  "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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