Model save

README.md

@@ -0,0 +1,88 @@
+---
+license: cc-by-sa-4.0
+base_model: retrieva-jp/t5-base-long
+tags:
+- generated_from_trainer
+datasets:
+- xlsum
+metrics:
+- rouge
+model-index:
+- name: t5-base-xlsum-ja
+  results:
+  - task:
+      name: Sequence-to-sequence Language Modeling
+      type: text2text-generation
+    dataset:
+      name: xlsum
+      type: xlsum
+      config: japanese
+      split: train
+      args: japanese
+    metrics:
+    - name: Rouge1
+      type: rouge
+      value: 0.3648008957585529
+---
+
+<!-- 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. -->
+
+# t5-base-xlsum-ja
+
+This model is a fine-tuned version of [retrieva-jp/t5-base-long](https://huggingface.co/retrieva-jp/t5-base-long) on the xlsum dataset.
+It achieves the following results on the evaluation set:
+- Loss: 2.6563
+- Rouge1: 0.3648
+- Rouge2: 0.1641
+- Rougel: 0.2965
+- Rougelsum: 0.3132
+
+## 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
+- gradient_accumulation_steps: 16
+- total_train_batch_size: 128
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_ratio: 0.01
+- num_epochs: 15
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
+|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
+| 4.9166        | 1.8   | 100  | 3.4095          | 0.3569 | 0.1509 | 0.2416 | 0.3209    |
+| 4.1162        | 3.61  | 200  | 3.0980          | 0.3262 | 0.1354 | 0.2557 | 0.2805    |
+| 3.8578        | 5.41  | 300  | 2.8853          | 0.3428 | 0.1445 | 0.2628 | 0.2881    |
+| 3.7309        | 7.22  | 400  | 2.7714          | 0.3621 | 0.1615 | 0.2951 | 0.3151    |
+| 3.6716        | 9.02  | 500  | 2.7042          | 0.3727 | 0.1668 | 0.2982 | 0.3225    |
+| 3.6393        | 10.82 | 600  | 2.6666          | 0.3676 | 0.1592 | 0.2987 | 0.3206    |
+| 3.6291        | 12.63 | 700  | 2.6587          | 0.3654 | 0.1576 | 0.2955 | 0.3108    |
+| 3.6224        | 14.43 | 800  | 2.6563          | 0.3648 | 0.1641 | 0.2965 | 0.3132    |
+
+
+### Framework versions
+
+- Transformers 4.34.0
+- Pytorch 2.0.0+cu118
+- Datasets 2.14.5
+- Tokenizers 0.14.0

generation_config.json

@@ -0,0 +1,9 @@
+{
+  "decoder_start_token_id": 0,
+  "eos_token_id": 1,
+  "max_length": 128,
+  "no_repeat_ngram_size": 2,
+  "num_beams": 15,
+  "pad_token_id": 0,
+  "transformers_version": "4.34.0"
+}

pytorch_model.bin

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:e476eddec0fb7a1cf4985ace419f38a1a33620f8375897e7c6447a2283b4563a
+oid sha256:cb70eb98c3ad2fafe4a30430240046249ed786073e6e23d23b525fcddc6892bb
 size 495253173