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bart-large-cnndm

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bart
text2text-generation
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  1. README.md +110 -0
  2. cnn_dailymail_726_bart-large/config.json +74 -0
  3. cnn_dailymail_726_bart-large/generation_config.json +12 -0
  4. cnn_dailymail_726_bart-large/merges.txt +0 -0
  5. cnn_dailymail_726_bart-large/model.safetensors +3 -0
  6. cnn_dailymail_726_bart-large/special_tokens_map.json +15 -0
  7. cnn_dailymail_726_bart-large/tokenizer.json +0 -0
  8. cnn_dailymail_726_bart-large/tokenizer_config.json +57 -0
  9. cnn_dailymail_726_bart-large/training_args.bin +3 -0
  10. cnn_dailymail_726_bart-large/vocab.json +0 -0
  11. config.json +74 -0
  12. generation_config.json +12 -0
  13. merges.txt +0 -0
  14. model.safetensors +3 -0
  15. special_tokens_map.json +15 -0
  16. tokenizer.json +0 -0
  17. tokenizer_config.json +57 -0
  18. training_args.bin +3 -0
  19. vocab.json +0 -0
  20. xsum_1677_bart-base/config.json +75 -0
  21. xsum_1677_bart-base/generation_config.json +12 -0
  22. xsum_1677_bart-base/merges.txt +0 -0
  23. xsum_1677_bart-base/model.safetensors +3 -0
  24. xsum_1677_bart-base/special_tokens_map.json +15 -0
  25. xsum_1677_bart-base/tokenizer.json +0 -0
  26. xsum_1677_bart-base/tokenizer_config.json +57 -0
  27. xsum_1677_bart-base/training_args.bin +3 -0
  28. xsum_1677_bart-base/vocab.json +0 -0
README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: facebook/bart-large
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - rouge
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+ model-index:
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+ - name: cnn_dailymail_726_bart-large
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+ results: []
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # cnn_dailymail_726_bart-large
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+
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+ This model is a fine-tuned version of [facebook/bart-large](https://huggingface.co/facebook/bart-large) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.8412
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+ - Rouge1: 0.2469
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+ - Rouge2: 0.1266
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+ - Rougel: 0.2074
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+ - Rougelsum: 0.2332
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+ - Gen Len: 20.0
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 5e-05
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+ - train_batch_size: 8
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+ - eval_batch_size: 8
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+ - seed: 42
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+ - gradient_accumulation_steps: 16
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+ - total_train_batch_size: 128
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - lr_scheduler_warmup_steps: 500
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+ - num_epochs: 10
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
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+ |:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
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+ | 0.9706 | 0.22 | 500 | 0.9015 | 0.237 | 0.1181 | 0.1979 | 0.2232 | 19.9999 |
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+ | 0.9212 | 0.45 | 1000 | 0.8771 | 0.237 | 0.1193 | 0.199 | 0.2233 | 20.0 |
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+ | 0.8991 | 0.67 | 1500 | 0.8572 | 0.2443 | 0.1238 | 0.2045 | 0.2304 | 20.0 |
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+ | 0.9085 | 0.89 | 2000 | 0.8519 | 0.2404 | 0.1227 | 0.2022 | 0.2269 | 20.0 |
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+ | 0.8494 | 1.11 | 2500 | 0.8471 | 0.2437 | 0.1233 | 0.2041 | 0.2298 | 20.0 |
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+ | 0.832 | 1.34 | 3000 | 0.8400 | 0.2438 | 0.1248 | 0.2055 | 0.2301 | 20.0 |
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+ | 0.8522 | 1.56 | 3500 | 0.8393 | 0.2417 | 0.1242 | 0.2043 | 0.2283 | 20.0 |
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+ | 0.8494 | 1.78 | 4000 | 0.8338 | 0.2436 | 0.1239 | 0.2047 | 0.23 | 19.9999 |
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+ | 0.7729 | 2.01 | 4500 | 0.8332 | 0.2431 | 0.1253 | 0.2048 | 0.2298 | 20.0 |
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+ | 0.7761 | 2.23 | 5000 | 0.8323 | 0.2477 | 0.1264 | 0.207 | 0.2335 | 19.9994 |
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+ | 0.7788 | 2.45 | 5500 | 0.8277 | 0.2473 | 0.1259 | 0.2068 | 0.2333 | 20.0 |
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+ | 0.7832 | 2.67 | 6000 | 0.8251 | 0.2453 | 0.126 | 0.2061 | 0.2317 | 20.0 |
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+ | 0.7888 | 2.9 | 6500 | 0.8239 | 0.242 | 0.1241 | 0.2037 | 0.2287 | 20.0 |
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+ | 0.7413 | 3.12 | 7000 | 0.8360 | 0.2394 | 0.1228 | 0.2017 | 0.2258 | 20.0 |
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+ | 0.7438 | 3.34 | 7500 | 0.8283 | 0.2462 | 0.1267 | 0.2072 | 0.2326 | 19.9999 |
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+ | 0.7271 | 3.57 | 8000 | 0.8275 | 0.2406 | 0.1235 | 0.2028 | 0.2276 | 20.0 |
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+ | 0.7435 | 3.79 | 8500 | 0.8221 | 0.2451 | 0.1254 | 0.2055 | 0.2311 | 19.9998 |
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+ | 0.7072 | 4.01 | 9000 | 0.8277 | 0.2437 | 0.1251 | 0.2049 | 0.2301 | 19.9999 |
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+ | 0.708 | 4.24 | 9500 | 0.8270 | 0.2465 | 0.1263 | 0.2067 | 0.2325 | 19.9999 |
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+ | 0.7058 | 4.46 | 10000 | 0.8279 | 0.2424 | 0.1249 | 0.2045 | 0.229 | 19.9999 |
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+ | 0.6918 | 4.68 | 10500 | 0.8248 | 0.246 | 0.1259 | 0.2063 | 0.232 | 19.9998 |
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+ | 0.7121 | 4.9 | 11000 | 0.8231 | 0.2457 | 0.126 | 0.2058 | 0.232 | 19.9999 |
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+ | 0.6667 | 5.13 | 11500 | 0.8297 | 0.2458 | 0.1262 | 0.2066 | 0.2323 | 19.9996 |
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+ | 0.6767 | 5.35 | 12000 | 0.8309 | 0.2469 | 0.1269 | 0.2071 | 0.2332 | 19.9996 |
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+ | 0.6961 | 5.57 | 12500 | 0.8299 | 0.247 | 0.1271 | 0.2074 | 0.2333 | 20.0 |
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+ | 0.6842 | 5.8 | 13000 | 0.8333 | 0.2473 | 0.127 | 0.2077 | 0.2336 | 19.9996 |
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+ | 0.6485 | 6.02 | 13500 | 0.8360 | 0.2454 | 0.1259 | 0.2061 | 0.2316 | 19.9998 |
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+ | 0.6651 | 6.24 | 14000 | 0.8349 | 0.2454 | 0.126 | 0.2062 | 0.2314 | 20.0 |
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+ | 0.6483 | 6.46 | 14500 | 0.8331 | 0.2454 | 0.1258 | 0.2058 | 0.2316 | 20.0 |
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+ | 0.6626 | 6.69 | 15000 | 0.8309 | 0.2468 | 0.127 | 0.2069 | 0.2328 | 19.9996 |
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+ | 0.6675 | 6.91 | 15500 | 0.8337 | 0.2448 | 0.1255 | 0.2056 | 0.231 | 19.9999 |
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+ | 0.6479 | 7.13 | 16000 | 0.8387 | 0.2471 | 0.1267 | 0.2074 | 0.2333 | 19.9999 |
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+ | 0.6506 | 7.36 | 16500 | 0.8377 | 0.2474 | 0.1264 | 0.2071 | 0.2335 | 19.9999 |
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+ | 0.643 | 7.58 | 17000 | 0.8369 | 0.2454 | 0.1259 | 0.2059 | 0.2318 | 20.0 |
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+ | 0.6262 | 7.8 | 17500 | 0.8378 | 0.2466 | 0.1269 | 0.2071 | 0.233 | 19.9997 |
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+ | 0.6235 | 8.02 | 18000 | 0.8415 | 0.2458 | 0.1266 | 0.2065 | 0.2321 | 20.0 |
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+ | 0.6081 | 8.25 | 18500 | 0.8421 | 0.2465 | 0.1267 | 0.2069 | 0.2326 | 19.9997 |
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+ | 0.6257 | 8.47 | 19000 | 0.8409 | 0.2477 | 0.1267 | 0.2075 | 0.2337 | 19.9999 |
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+ | 0.6187 | 8.69 | 19500 | 0.8381 | 0.2459 | 0.1264 | 0.2066 | 0.2321 | 19.9997 |
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+ | 0.6178 | 8.92 | 20000 | 0.8384 | 0.248 | 0.1273 | 0.2079 | 0.2339 | 19.9996 |
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+ | 0.6018 | 9.14 | 20500 | 0.8432 | 0.2468 | 0.1265 | 0.2071 | 0.2329 | 20.0 |
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+ | 0.6235 | 9.36 | 21000 | 0.8418 | 0.2469 | 0.1265 | 0.207 | 0.233 | 20.0 |
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+ | 0.606 | 9.58 | 21500 | 0.8418 | 0.2464 | 0.1264 | 0.207 | 0.2327 | 19.9999 |
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+ | 0.6016 | 9.81 | 22000 | 0.8412 | 0.2469 | 0.1266 | 0.2074 | 0.2332 | 20.0 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.37.2
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+ - Pytorch 2.2.0+cu121
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+ - Datasets 2.16.1
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+ - Tokenizers 0.15.1
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+ "use_cache": true,
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+ "vocab_size": 50265
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