Model save

README.md

@@ -0,0 +1,99 @@
+---
+base_model: google/pegasus-xsum
+tags:
+- generated_from_trainer
+datasets:
+- samsum
+metrics:
+- rouge
+- precision
+- recall
+- f1
+model-index:
+- name: Pegasus_xsum_samsum
+  results:
+  - task:
+      name: Sequence-to-sequence Language Modeling
+      type: text2text-generation
+    dataset:
+      name: samsum
+      type: samsum
+      config: samsum
+      split: validation
+      args: samsum
+    metrics:
+    - name: Rouge1
+      type: rouge
+      value: 0.5072
+    - name: Precision
+      type: precision
+      value: 0.9247
+    - name: Recall
+      type: recall
+      value: 0.9099
+    - name: F1
+      type: f1
+      value: 0.917
+---
+
+<!-- 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. -->
+
+# Pegasus_xsum_samsum
+
+This model is a fine-tuned version of [google/pegasus-xsum](https://huggingface.co/google/pegasus-xsum) on the samsum dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.4709
+- Rouge1: 0.5072
+- Rouge2: 0.2631
+- Rougel: 0.4243
+- Rougelsum: 0.4244
+- Gen Len: 19.1479
+- Precision: 0.9247
+- Recall: 0.9099
+- F1: 0.917
+
+## 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: 2e-05
+- train_batch_size: 4
+- eval_batch_size: 4
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 16
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 4
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | Precision | Recall | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|:---------:|:------:|:------:|
+| 1.9542        | 1.0   | 920  | 1.5350          | 0.4928 | 0.2436 | 0.4085 | 0.4086    | 18.5672 | 0.9229    | 0.9074 | 0.9149 |
+| 1.6331        | 2.0   | 1841 | 1.4914          | 0.5037 | 0.257  | 0.4202 | 0.4206    | 18.8154 | 0.9246    | 0.9092 | 0.9166 |
+| 1.5694        | 3.0   | 2762 | 1.4761          | 0.5071 | 0.259  | 0.4212 | 0.4214    | 19.4487 | 0.9241    | 0.9103 | 0.917  |
+| 1.5374        | 4.0   | 3680 | 1.4709          | 0.5072 | 0.2631 | 0.4243 | 0.4244    | 19.1479 | 0.9247    | 0.9099 | 0.917  |
+
+
+### Framework versions
+
+- Transformers 4.36.0
+- Pytorch 2.0.1+cu117
+- Datasets 2.14.5
+- Tokenizers 0.15.0

generation_config.json

@@ -0,0 +1,11 @@
+{
+  "bos_token_id": 0,
+  "decoder_start_token_id": 0,
+  "eos_token_id": 1,
+  "forced_eos_token_id": 1,
+  "length_penalty": 0.6,
+  "max_length": 64,
+  "num_beams": 8,
+  "pad_token_id": 0,
+  "transformers_version": "4.36.0"
+}

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:42c28efe74cc339edb90ec0d9e446c806d8af9d331f4041d8bfe61b85ffe7c9c
+oid sha256:14147f92302869d444c720356b6c1263f091e779662754de20a5bce0b2eb0ee8
 size 2279458540

runs/Feb02_13-43-49_o8amirctr1706761897220-scx9w/events.out.tfevents.1706852634.o8amirctr1706761897220-scx9w.28324.0

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:b0c7160e7db54d16ce8267382c3deb946ba292f772319c82fd397ceff82b83c5
-size 8393
+oid sha256:2caadc6e993654c43fad2a2f1a52febf281d1097b5ad573259145f6110e1c4b9
+size 9421