trainer: training complete at 2024-01-28 12:28:03.218291.

README.md

@@ -3,11 +3,26 @@ license: apache-2.0
 base_model: allenai/longformer-base-4096
 tags:
 - generated_from_trainer
+datasets:
+- fancy_dataset
 metrics:
 - accuracy
 model-index:
 - name: longformer-one-step
-  results: []
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: fancy_dataset
+      type: fancy_dataset
+      config: full_labels
+      split: test
+      args: full_labels
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.8056899208140743
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -15,19 +30,19 @@ should probably proofread and complete it, then remove this comment. -->
 
 # longformer-one-step
 
-This model is a fine-tuned version of [allenai/longformer-base-4096](https://huggingface.co/allenai/longformer-base-4096) on the None dataset.
+This model is a fine-tuned version of [allenai/longformer-base-4096](https://huggingface.co/allenai/longformer-base-4096) on the fancy_dataset dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.6204
-- B-claim: {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 147.0}
-- B-majorclaim: {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 77.0}
-- B-premise: {'precision': 0.6069364161849711, 'recall': 0.5526315789473685, 'f1-score': 0.5785123966942148, 'support': 380.0}
-- I-claim: {'precision': 0.5083841463414634, 'recall': 0.3100883310088331, 'f1-score': 0.3852151313889692, 'support': 2151.0}
-- I-majorclaim: {'precision': 0.4941275167785235, 'recall': 0.562559694364852, 'f1-score': 0.5261277355962484, 'support': 1047.0}
-- I-premise: {'precision': 0.8047369129323106, 'recall': 0.9100593516968498, 'f1-score': 0.8541636909012997, 'support': 6571.0}
-- O: {'precision': 0.854797733046707, 'recall': 0.8704477611940299, 'f1-score': 0.862551764937882, 'support': 5025.0}
-- Accuracy: 0.7676
-- Macro avg: {'precision': 0.46699753218342505, 'recall': 0.45796953103027616, 'f1-score': 0.45808153135980195, 'support': 15398.0}
-- Weighted avg: {'precision': 0.7419669119649179, 'recall': 0.7676321600207819, 'f1-score': 0.74985845104923, 'support': 15398.0}
+- Loss: 0.5149
+- B-claim: {'precision': 1.0, 'recall': 0.0036101083032490976, 'f1-score': 0.007194244604316546, 'support': 277.0}
+- B-majorclaim: {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 141.0}
+- B-premise: {'precision': 0.5939759036144578, 'recall': 0.7691107644305772, 'f1-score': 0.6702923181509177, 'support': 641.0}
+- I-claim: {'precision': 0.5709936340990867, 'recall': 0.5057612159843099, 'f1-score': 0.5364014560582424, 'support': 4079.0}
+- I-majorclaim: {'precision': 0.6075593084036992, 'recall': 0.7403233708966193, 'f1-score': 0.6674028268551236, 'support': 2041.0}
+- I-premise: {'precision': 0.8469945355191257, 'recall': 0.8930597992143169, 'f1-score': 0.8694174138443888, 'support': 11455.0}
+- O: {'precision': 0.92, 'recall': 0.8828032345013477, 'f1-score': 0.9010178817056397, 'support': 9275.0}
+- Accuracy: 0.8057
+- Macro avg: {'precision': 0.6485033402337671, 'recall': 0.5420954990472029, 'f1-score': 0.5216751630312327, 'support': 27909.0}
+- Weighted avg: {'precision': 0.8048361654136865, 'recall': 0.8056899208140743, 'f1-score': 0.7989508122458809, 'support': 27909.0}
 
 ## Model description
 
@@ -56,16 +71,16 @@ The following hyperparameters were used during training:
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss | B-claim                                                              | B-majorclaim                                                        | B-premise                                                                                                          | I-claim                                                                                                              | I-majorclaim                                                                                                        | I-premise                                                                                                          | O                                                                                                                  | Accuracy | Macro avg                                                                                                              | Weighted avg                                                                                                        |
-|:-------------:|:-----:|:----:|:---------------:|:--------------------------------------------------------------------:|:-------------------------------------------------------------------:|:------------------------------------------------------------------------------------------------------------------:|:--------------------------------------------------------------------------------------------------------------------:|:-------------------------------------------------------------------------------------------------------------------:|:------------------------------------------------------------------------------------------------------------------:|:------------------------------------------------------------------------------------------------------------------:|:--------:|:----------------------------------------------------------------------------------------------------------------------:|:-------------------------------------------------------------------------------------------------------------------:|
-| No log        | 1.0   | 36   | 0.8375          | {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 147.0} | {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 77.0} | {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 380.0}                                               | {'precision': 0.3307174887892377, 'recall': 0.13714551371455136, 'f1-score': 0.1938876109102859, 'support': 2151.0}  | {'precision': 0.25, 'recall': 0.0009551098376313276, 'f1-score': 0.0019029495718363464, 'support': 1047.0}          | {'precision': 0.6899198931909212, 'recall': 0.9436919799117334, 'f1-score': 0.7970949289800116, 'support': 6571.0} | {'precision': 0.7767500906782735, 'recall': 0.8523383084577114, 'f1-score': 0.8127905873422525, 'support': 5025.0} | 0.7001   | {'precision': 0.29248392466549034, 'recall': 0.2763044159888039, 'f1-score': 0.25795372525776944, 'support': 15398.0}  | {'precision': 0.6111024900767319, 'recall': 0.7000909208988181, 'f1-score': 0.6326164514217569, 'support': 15398.0} |
-| No log        | 2.0   | 72   | 0.6930          | {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 147.0} | {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 77.0} | {'precision': 0.6489795918367347, 'recall': 0.41842105263157897, 'f1-score': 0.5087999999999999, 'support': 380.0} | {'precision': 0.4376956793988729, 'recall': 0.32496513249651326, 'f1-score': 0.37299893276414087, 'support': 2151.0} | {'precision': 0.3946384039900249, 'recall': 0.6045845272206304, 'f1-score': 0.47755563938136547, 'support': 1047.0} | {'precision': 0.83792191631669, 'recall': 0.8198143357175468, 'f1-score': 0.8287692307692307, 'support': 6571.0}   | {'precision': 0.8073510773130546, 'recall': 0.887363184079602, 'f1-score': 0.8454683352294274, 'support': 5025.0}  | 0.7363   | {'precision': 0.446655238407911, 'recall': 0.4364497474494102, 'f1-score': 0.4333703054491663, 'support': 15398.0}     | {'precision': 0.7250426117598104, 'recall': 0.7362644499285621, 'f1-score': 0.7267168761345917, 'support': 15398.0} |
-| No log        | 3.0   | 108  | 0.6204          | {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 147.0} | {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 77.0} | {'precision': 0.6069364161849711, 'recall': 0.5526315789473685, 'f1-score': 0.5785123966942148, 'support': 380.0}  | {'precision': 0.5083841463414634, 'recall': 0.3100883310088331, 'f1-score': 0.3852151313889692, 'support': 2151.0}   | {'precision': 0.4941275167785235, 'recall': 0.562559694364852, 'f1-score': 0.5261277355962484, 'support': 1047.0}   | {'precision': 0.8047369129323106, 'recall': 0.9100593516968498, 'f1-score': 0.8541636909012997, 'support': 6571.0} | {'precision': 0.854797733046707, 'recall': 0.8704477611940299, 'f1-score': 0.862551764937882, 'support': 5025.0}   | 0.7676   | {'precision': 0.46699753218342505, 'recall': 0.45796953103027616, 'f1-score': 0.45808153135980195, 'support': 15398.0} | {'precision': 0.7419669119649179, 'recall': 0.7676321600207819, 'f1-score': 0.74985845104923, 'support': 15398.0}   |
+| Training Loss | Epoch | Step | Validation Loss | B-claim                                                                                                 | B-majorclaim                                                         | B-premise                                                                                                         | I-claim                                                                                                             | I-majorclaim                                                                                                           | I-premise                                                                                                           | O                                                                                                                  | Accuracy | Macro avg                                                                                                             | Weighted avg                                                                                                        |
+|:-------------:|:-----:|:----:|:---------------:|:-------------------------------------------------------------------------------------------------------:|:--------------------------------------------------------------------:|:-----------------------------------------------------------------------------------------------------------------:|:-------------------------------------------------------------------------------------------------------------------:|:----------------------------------------------------------------------------------------------------------------------:|:-------------------------------------------------------------------------------------------------------------------:|:------------------------------------------------------------------------------------------------------------------:|:--------:|:---------------------------------------------------------------------------------------------------------------------:|:-------------------------------------------------------------------------------------------------------------------:|
+| No log        | 1.0   | 41   | 0.7274          | {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 277.0}                                    | {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 141.0} | {'precision': 0.78, 'recall': 0.060842433697347896, 'f1-score': 0.11287988422575977, 'support': 641.0}            | {'precision': 0.36033007334963324, 'recall': 0.28904143172346164, 'f1-score': 0.320772683988573, 'support': 4079.0} | {'precision': 0.5909090909090909, 'recall': 0.012738853503184714, 'f1-score': 0.024940047961630695, 'support': 2041.0} | {'precision': 0.7395335962909141, 'recall': 0.9329550414666085, 'f1-score': 0.8250598316992201, 'support': 11455.0} | {'precision': 0.8197582243361078, 'recall': 0.8919676549865229, 'f1-score': 0.8543398564568596, 'support': 9275.0} | 0.7239   | {'precision': 0.47007585498367804, 'recall': 0.3125064879110179, 'f1-score': 0.30542747204743476, 'support': 27909.0} | {'precision': 0.6897569493700394, 'recall': 0.7239241821634598, 'f1-score': 0.6738597929850489, 'support': 27909.0} |
+| No log        | 2.0   | 82   | 0.5478          | {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 277.0}                                    | {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 141.0} | {'precision': 0.6131687242798354, 'recall': 0.6973478939157566, 'f1-score': 0.6525547445255474, 'support': 641.0} | {'precision': 0.553030303030303, 'recall': 0.4295170384898259, 'f1-score': 0.48351041810404305, 'support': 4079.0}  | {'precision': 0.6469656992084433, 'recall': 0.600685938265556, 'f1-score': 0.6229674796747968, 'support': 2041.0}      | {'precision': 0.8183098591549296, 'recall': 0.9129637712789175, 'f1-score': 0.8630493088508355, 'support': 11455.0} | {'precision': 0.8851879618721217, 'recall': 0.8911051212938005, 'f1-score': 0.8881366860090264, 'support': 9275.0} | 0.7936   | {'precision': 0.5023803639350904, 'recall': 0.5045171090348366, 'f1-score': 0.5014598053091784, 'support': 27909.0}   | {'precision': 0.7722658115085478, 'recall': 0.7935791321795836, 'f1-score': 0.7805976856327196, 'support': 27909.0} |
+| No log        | 3.0   | 123  | 0.5149          | {'precision': 1.0, 'recall': 0.0036101083032490976, 'f1-score': 0.007194244604316546, 'support': 277.0} | {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 141.0} | {'precision': 0.5939759036144578, 'recall': 0.7691107644305772, 'f1-score': 0.6702923181509177, 'support': 641.0} | {'precision': 0.5709936340990867, 'recall': 0.5057612159843099, 'f1-score': 0.5364014560582424, 'support': 4079.0}  | {'precision': 0.6075593084036992, 'recall': 0.7403233708966193, 'f1-score': 0.6674028268551236, 'support': 2041.0}     | {'precision': 0.8469945355191257, 'recall': 0.8930597992143169, 'f1-score': 0.8694174138443888, 'support': 11455.0} | {'precision': 0.92, 'recall': 0.8828032345013477, 'f1-score': 0.9010178817056397, 'support': 9275.0}               | 0.8057   | {'precision': 0.6485033402337671, 'recall': 0.5420954990472029, 'f1-score': 0.5216751630312327, 'support': 27909.0}   | {'precision': 0.8048361654136865, 'recall': 0.8056899208140743, 'f1-score': 0.7989508122458809, 'support': 27909.0} |
 
 
 ### Framework versions
 
-- Transformers 4.33.0
-- Pytorch 2.0.1+cu118
-- Datasets 2.14.4
-- Tokenizers 0.13.3
+- Transformers 4.37.1
+- Pytorch 2.1.2+cu121
+- Datasets 2.16.1
+- Tokenizers 0.15.1

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:b0d846a9d1c06fd4281cd93a6411a1bdd691aef078a4937c3e724dcd700e2ac5
+oid sha256:4b1e4d35674ddf16530c959254233ea38164751f68cd02d9fb573be1cace4b87
 size 592330980