Farouk commited on
Commit
df63e7e
·
1 Parent(s): 6ecf6e1

Training in progress, step 9600

Browse files
adapter_model.bin CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:7490cbc45e1576aca6da2aa2586233a3feb26c8e67c39319fd7fddd5ecc52db4
3
  size 319977229
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:7b4a2da828c293af067c6de1ed58b33b65a1f97aee2e6e70e7280cc2d785544e
3
  size 319977229
checkpoint-4200/adapter_model/adapter_model/README.md CHANGED
@@ -279,6 +279,17 @@ The following `bitsandbytes` quantization config was used during training:
279
  - bnb_4bit_use_double_quant: True
280
  - bnb_4bit_compute_dtype: bfloat16
281
 
 
 
 
 
 
 
 
 
 
 
 
282
  The following `bitsandbytes` quantization config was used during training:
283
  - load_in_8bit: False
284
  - load_in_4bit: True
@@ -316,5 +327,6 @@ The following `bitsandbytes` quantization config was used during training:
316
  - PEFT 0.4.0
317
  - PEFT 0.4.0
318
  - PEFT 0.4.0
 
319
 
320
  - PEFT 0.4.0
 
279
  - bnb_4bit_use_double_quant: True
280
  - bnb_4bit_compute_dtype: bfloat16
281
 
282
+ The following `bitsandbytes` quantization config was used during training:
283
+ - load_in_8bit: False
284
+ - load_in_4bit: True
285
+ - llm_int8_threshold: 6.0
286
+ - llm_int8_skip_modules: None
287
+ - llm_int8_enable_fp32_cpu_offload: False
288
+ - llm_int8_has_fp16_weight: False
289
+ - bnb_4bit_quant_type: nf4
290
+ - bnb_4bit_use_double_quant: True
291
+ - bnb_4bit_compute_dtype: bfloat16
292
+
293
  The following `bitsandbytes` quantization config was used during training:
294
  - load_in_8bit: False
295
  - load_in_4bit: True
 
327
  - PEFT 0.4.0
328
  - PEFT 0.4.0
329
  - PEFT 0.4.0
330
+ - PEFT 0.4.0
331
 
332
  - PEFT 0.4.0
checkpoint-4200/adapter_model/adapter_model/adapter_model.bin CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:bd8ff3cfeedffac6ed43bbf95d18452e64953fab891ba988d2e7690cc29751ec
3
  size 319977229
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:7490cbc45e1576aca6da2aa2586233a3feb26c8e67c39319fd7fddd5ecc52db4
3
  size 319977229
{checkpoint-7600 → checkpoint-9600}/README.md RENAMED
File without changes
{checkpoint-7600 → checkpoint-9600}/adapter_config.json RENAMED
File without changes
{checkpoint-7600 → checkpoint-9600}/adapter_model.bin RENAMED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:e5218ffd08edf8036e6b27f82b1aa7697bf58373c87a86d85e77b7e03b1c2a18
3
  size 319977229
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:7b4a2da828c293af067c6de1ed58b33b65a1f97aee2e6e70e7280cc2d785544e
3
  size 319977229
{checkpoint-7600 → checkpoint-9600}/added_tokens.json RENAMED
File without changes
{checkpoint-7600 → checkpoint-9600}/optimizer.pt RENAMED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:3438f6c51a636ac6bd76253a693835c05b7035953cca8b0f3dcb053bca090a55
3
  size 1279539973
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:c4aa05a9425588ee0421861e1f0a81321c03c5c0626e5c4e87e260993227c31d
3
  size 1279539973
{checkpoint-7600 → checkpoint-9600}/rng_state.pth RENAMED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:36961bbfa7c61f6516a16f1cef17fc66bd42e7ce35c5d6452e9c57ec9d0afde4
3
  size 14511
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:49ca17e2eebe44ae19e6bcd9f2565c421bdda73f807742623cc2644a3e84f9a3
3
  size 14511
{checkpoint-7600 → checkpoint-9600}/scheduler.pt RENAMED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:28e84ce1056e951be7d81d2edd8521bf4fd1356b40fedd4b87bf74e02969be5b
3
  size 627
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:0b730b5465fd4d5b685fb0c0a2d7cb7400a28391a16b7e3e188b846bcfacab04
3
  size 627
{checkpoint-7600 → checkpoint-9600}/special_tokens_map.json RENAMED
File without changes
{checkpoint-7600 → checkpoint-9600}/tokenizer.model RENAMED
File without changes
{checkpoint-7600 → checkpoint-9600}/tokenizer_config.json RENAMED
File without changes
{checkpoint-7600 → checkpoint-9600}/trainer_state.json RENAMED
@@ -1,8 +1,8 @@
1
  {
2
  "best_metric": 1.0316325426101685,
3
  "best_model_checkpoint": "experts/expert-7/checkpoint-4200",
4
- "epoch": 3.440470801267542,
5
- "global_step": 7600,
6
  "is_hyper_param_search": false,
7
  "is_local_process_zero": true,
8
  "is_world_process_zero": true,
@@ -7264,11 +7264,1921 @@
7264
  "mmlu_eval_accuracy_world_religions": 0.7894736842105263,
7265
  "mmlu_loss": 1.291005614726724,
7266
  "step": 7600
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
7267
  }
7268
  ],
7269
  "max_steps": 10000,
7270
  "num_train_epochs": 5,
7271
- "total_flos": 2.714140024730321e+18,
7272
  "trial_name": null,
7273
  "trial_params": null
7274
  }
 
1
  {
2
  "best_metric": 1.0316325426101685,
3
  "best_model_checkpoint": "experts/expert-7/checkpoint-4200",
4
+ "epoch": 4.345857854232684,
5
+ "global_step": 9600,
6
  "is_hyper_param_search": false,
7
  "is_local_process_zero": true,
8
  "is_world_process_zero": true,
 
7264
  "mmlu_eval_accuracy_world_religions": 0.7894736842105263,
7265
  "mmlu_loss": 1.291005614726724,
7266
  "step": 7600
7267
+ },
7268
+ {
7269
+ "epoch": 3.44,
7270
+ "learning_rate": 0.0002,
7271
+ "loss": 0.7426,
7272
+ "step": 7610
7273
+ },
7274
+ {
7275
+ "epoch": 3.45,
7276
+ "learning_rate": 0.0002,
7277
+ "loss": 0.6424,
7278
+ "step": 7620
7279
+ },
7280
+ {
7281
+ "epoch": 3.45,
7282
+ "learning_rate": 0.0002,
7283
+ "loss": 0.8097,
7284
+ "step": 7630
7285
+ },
7286
+ {
7287
+ "epoch": 3.46,
7288
+ "learning_rate": 0.0002,
7289
+ "loss": 0.7112,
7290
+ "step": 7640
7291
+ },
7292
+ {
7293
+ "epoch": 3.46,
7294
+ "learning_rate": 0.0002,
7295
+ "loss": 0.7544,
7296
+ "step": 7650
7297
+ },
7298
+ {
7299
+ "epoch": 3.47,
7300
+ "learning_rate": 0.0002,
7301
+ "loss": 0.7586,
7302
+ "step": 7660
7303
+ },
7304
+ {
7305
+ "epoch": 3.47,
7306
+ "learning_rate": 0.0002,
7307
+ "loss": 0.7623,
7308
+ "step": 7670
7309
+ },
7310
+ {
7311
+ "epoch": 3.48,
7312
+ "learning_rate": 0.0002,
7313
+ "loss": 0.6811,
7314
+ "step": 7680
7315
+ },
7316
+ {
7317
+ "epoch": 3.48,
7318
+ "learning_rate": 0.0002,
7319
+ "loss": 0.7471,
7320
+ "step": 7690
7321
+ },
7322
+ {
7323
+ "epoch": 3.49,
7324
+ "learning_rate": 0.0002,
7325
+ "loss": 0.7105,
7326
+ "step": 7700
7327
+ },
7328
+ {
7329
+ "epoch": 3.49,
7330
+ "learning_rate": 0.0002,
7331
+ "loss": 0.7718,
7332
+ "step": 7710
7333
+ },
7334
+ {
7335
+ "epoch": 3.49,
7336
+ "learning_rate": 0.0002,
7337
+ "loss": 0.6904,
7338
+ "step": 7720
7339
+ },
7340
+ {
7341
+ "epoch": 3.5,
7342
+ "learning_rate": 0.0002,
7343
+ "loss": 0.6791,
7344
+ "step": 7730
7345
+ },
7346
+ {
7347
+ "epoch": 3.5,
7348
+ "learning_rate": 0.0002,
7349
+ "loss": 0.6911,
7350
+ "step": 7740
7351
+ },
7352
+ {
7353
+ "epoch": 3.51,
7354
+ "learning_rate": 0.0002,
7355
+ "loss": 0.7351,
7356
+ "step": 7750
7357
+ },
7358
+ {
7359
+ "epoch": 3.51,
7360
+ "learning_rate": 0.0002,
7361
+ "loss": 0.7143,
7362
+ "step": 7760
7363
+ },
7364
+ {
7365
+ "epoch": 3.52,
7366
+ "learning_rate": 0.0002,
7367
+ "loss": 0.7219,
7368
+ "step": 7770
7369
+ },
7370
+ {
7371
+ "epoch": 3.52,
7372
+ "learning_rate": 0.0002,
7373
+ "loss": 0.6999,
7374
+ "step": 7780
7375
+ },
7376
+ {
7377
+ "epoch": 3.53,
7378
+ "learning_rate": 0.0002,
7379
+ "loss": 0.6962,
7380
+ "step": 7790
7381
+ },
7382
+ {
7383
+ "epoch": 3.53,
7384
+ "learning_rate": 0.0002,
7385
+ "loss": 0.7188,
7386
+ "step": 7800
7387
+ },
7388
+ {
7389
+ "epoch": 3.53,
7390
+ "eval_loss": 1.0986956357955933,
7391
+ "eval_runtime": 130.3908,
7392
+ "eval_samples_per_second": 7.669,
7393
+ "eval_steps_per_second": 3.835,
7394
+ "step": 7800
7395
+ },
7396
+ {
7397
+ "epoch": 3.53,
7398
+ "mmlu_eval_accuracy": 0.5129068178429581,
7399
+ "mmlu_eval_accuracy_abstract_algebra": 0.2727272727272727,
7400
+ "mmlu_eval_accuracy_anatomy": 0.5714285714285714,
7401
+ "mmlu_eval_accuracy_astronomy": 0.625,
7402
+ "mmlu_eval_accuracy_business_ethics": 0.45454545454545453,
7403
+ "mmlu_eval_accuracy_clinical_knowledge": 0.5862068965517241,
7404
+ "mmlu_eval_accuracy_college_biology": 0.375,
7405
+ "mmlu_eval_accuracy_college_chemistry": 0.25,
7406
+ "mmlu_eval_accuracy_college_computer_science": 0.45454545454545453,
7407
+ "mmlu_eval_accuracy_college_mathematics": 0.2727272727272727,
7408
+ "mmlu_eval_accuracy_college_medicine": 0.4090909090909091,
7409
+ "mmlu_eval_accuracy_college_physics": 0.5454545454545454,
7410
+ "mmlu_eval_accuracy_computer_security": 0.36363636363636365,
7411
+ "mmlu_eval_accuracy_conceptual_physics": 0.46153846153846156,
7412
+ "mmlu_eval_accuracy_econometrics": 0.25,
7413
+ "mmlu_eval_accuracy_electrical_engineering": 0.375,
7414
+ "mmlu_eval_accuracy_elementary_mathematics": 0.36585365853658536,
7415
+ "mmlu_eval_accuracy_formal_logic": 0.21428571428571427,
7416
+ "mmlu_eval_accuracy_global_facts": 0.4,
7417
+ "mmlu_eval_accuracy_high_school_biology": 0.53125,
7418
+ "mmlu_eval_accuracy_high_school_chemistry": 0.4090909090909091,
7419
+ "mmlu_eval_accuracy_high_school_computer_science": 0.6666666666666666,
7420
+ "mmlu_eval_accuracy_high_school_european_history": 0.6666666666666666,
7421
+ "mmlu_eval_accuracy_high_school_geography": 0.9090909090909091,
7422
+ "mmlu_eval_accuracy_high_school_government_and_politics": 0.6190476190476191,
7423
+ "mmlu_eval_accuracy_high_school_macroeconomics": 0.4186046511627907,
7424
+ "mmlu_eval_accuracy_high_school_mathematics": 0.27586206896551724,
7425
+ "mmlu_eval_accuracy_high_school_microeconomics": 0.4230769230769231,
7426
+ "mmlu_eval_accuracy_high_school_physics": 0.11764705882352941,
7427
+ "mmlu_eval_accuracy_high_school_psychology": 0.8,
7428
+ "mmlu_eval_accuracy_high_school_statistics": 0.4782608695652174,
7429
+ "mmlu_eval_accuracy_high_school_us_history": 0.7272727272727273,
7430
+ "mmlu_eval_accuracy_high_school_world_history": 0.6538461538461539,
7431
+ "mmlu_eval_accuracy_human_aging": 0.6956521739130435,
7432
+ "mmlu_eval_accuracy_human_sexuality": 0.5,
7433
+ "mmlu_eval_accuracy_international_law": 0.8461538461538461,
7434
+ "mmlu_eval_accuracy_jurisprudence": 0.5454545454545454,
7435
+ "mmlu_eval_accuracy_logical_fallacies": 0.6666666666666666,
7436
+ "mmlu_eval_accuracy_machine_learning": 0.09090909090909091,
7437
+ "mmlu_eval_accuracy_management": 0.7272727272727273,
7438
+ "mmlu_eval_accuracy_marketing": 0.8,
7439
+ "mmlu_eval_accuracy_medical_genetics": 0.9090909090909091,
7440
+ "mmlu_eval_accuracy_miscellaneous": 0.6744186046511628,
7441
+ "mmlu_eval_accuracy_moral_disputes": 0.47368421052631576,
7442
+ "mmlu_eval_accuracy_moral_scenarios": 0.24,
7443
+ "mmlu_eval_accuracy_nutrition": 0.7272727272727273,
7444
+ "mmlu_eval_accuracy_philosophy": 0.47058823529411764,
7445
+ "mmlu_eval_accuracy_prehistory": 0.45714285714285713,
7446
+ "mmlu_eval_accuracy_professional_accounting": 0.25806451612903225,
7447
+ "mmlu_eval_accuracy_professional_law": 0.32941176470588235,
7448
+ "mmlu_eval_accuracy_professional_medicine": 0.5161290322580645,
7449
+ "mmlu_eval_accuracy_professional_psychology": 0.463768115942029,
7450
+ "mmlu_eval_accuracy_public_relations": 0.5,
7451
+ "mmlu_eval_accuracy_security_studies": 0.5555555555555556,
7452
+ "mmlu_eval_accuracy_sociology": 0.7727272727272727,
7453
+ "mmlu_eval_accuracy_us_foreign_policy": 0.7272727272727273,
7454
+ "mmlu_eval_accuracy_virology": 0.5555555555555556,
7455
+ "mmlu_eval_accuracy_world_religions": 0.7894736842105263,
7456
+ "mmlu_loss": 1.1720976933019902,
7457
+ "step": 7800
7458
+ },
7459
+ {
7460
+ "epoch": 3.54,
7461
+ "learning_rate": 0.0002,
7462
+ "loss": 0.7186,
7463
+ "step": 7810
7464
+ },
7465
+ {
7466
+ "epoch": 3.54,
7467
+ "learning_rate": 0.0002,
7468
+ "loss": 0.6645,
7469
+ "step": 7820
7470
+ },
7471
+ {
7472
+ "epoch": 3.54,
7473
+ "learning_rate": 0.0002,
7474
+ "loss": 0.7719,
7475
+ "step": 7830
7476
+ },
7477
+ {
7478
+ "epoch": 3.55,
7479
+ "learning_rate": 0.0002,
7480
+ "loss": 0.7619,
7481
+ "step": 7840
7482
+ },
7483
+ {
7484
+ "epoch": 3.55,
7485
+ "learning_rate": 0.0002,
7486
+ "loss": 0.7767,
7487
+ "step": 7850
7488
+ },
7489
+ {
7490
+ "epoch": 3.56,
7491
+ "learning_rate": 0.0002,
7492
+ "loss": 0.7032,
7493
+ "step": 7860
7494
+ },
7495
+ {
7496
+ "epoch": 3.56,
7497
+ "learning_rate": 0.0002,
7498
+ "loss": 0.7684,
7499
+ "step": 7870
7500
+ },
7501
+ {
7502
+ "epoch": 3.57,
7503
+ "learning_rate": 0.0002,
7504
+ "loss": 0.6622,
7505
+ "step": 7880
7506
+ },
7507
+ {
7508
+ "epoch": 3.57,
7509
+ "learning_rate": 0.0002,
7510
+ "loss": 0.6993,
7511
+ "step": 7890
7512
+ },
7513
+ {
7514
+ "epoch": 3.58,
7515
+ "learning_rate": 0.0002,
7516
+ "loss": 0.6745,
7517
+ "step": 7900
7518
+ },
7519
+ {
7520
+ "epoch": 3.58,
7521
+ "learning_rate": 0.0002,
7522
+ "loss": 0.7236,
7523
+ "step": 7910
7524
+ },
7525
+ {
7526
+ "epoch": 3.59,
7527
+ "learning_rate": 0.0002,
7528
+ "loss": 0.7068,
7529
+ "step": 7920
7530
+ },
7531
+ {
7532
+ "epoch": 3.59,
7533
+ "learning_rate": 0.0002,
7534
+ "loss": 0.7284,
7535
+ "step": 7930
7536
+ },
7537
+ {
7538
+ "epoch": 3.59,
7539
+ "learning_rate": 0.0002,
7540
+ "loss": 0.7565,
7541
+ "step": 7940
7542
+ },
7543
+ {
7544
+ "epoch": 3.6,
7545
+ "learning_rate": 0.0002,
7546
+ "loss": 0.7618,
7547
+ "step": 7950
7548
+ },
7549
+ {
7550
+ "epoch": 3.6,
7551
+ "learning_rate": 0.0002,
7552
+ "loss": 0.6919,
7553
+ "step": 7960
7554
+ },
7555
+ {
7556
+ "epoch": 3.61,
7557
+ "learning_rate": 0.0002,
7558
+ "loss": 0.7632,
7559
+ "step": 7970
7560
+ },
7561
+ {
7562
+ "epoch": 3.61,
7563
+ "learning_rate": 0.0002,
7564
+ "loss": 0.7072,
7565
+ "step": 7980
7566
+ },
7567
+ {
7568
+ "epoch": 3.62,
7569
+ "learning_rate": 0.0002,
7570
+ "loss": 0.7988,
7571
+ "step": 7990
7572
+ },
7573
+ {
7574
+ "epoch": 3.62,
7575
+ "learning_rate": 0.0002,
7576
+ "loss": 0.6931,
7577
+ "step": 8000
7578
+ },
7579
+ {
7580
+ "epoch": 3.62,
7581
+ "eval_loss": 1.0916101932525635,
7582
+ "eval_runtime": 130.4702,
7583
+ "eval_samples_per_second": 7.665,
7584
+ "eval_steps_per_second": 3.832,
7585
+ "step": 8000
7586
+ },
7587
+ {
7588
+ "epoch": 3.62,
7589
+ "mmlu_eval_accuracy": 0.5105854802224947,
7590
+ "mmlu_eval_accuracy_abstract_algebra": 0.2727272727272727,
7591
+ "mmlu_eval_accuracy_anatomy": 0.5714285714285714,
7592
+ "mmlu_eval_accuracy_astronomy": 0.5,
7593
+ "mmlu_eval_accuracy_business_ethics": 0.45454545454545453,
7594
+ "mmlu_eval_accuracy_clinical_knowledge": 0.5862068965517241,
7595
+ "mmlu_eval_accuracy_college_biology": 0.375,
7596
+ "mmlu_eval_accuracy_college_chemistry": 0.625,
7597
+ "mmlu_eval_accuracy_college_computer_science": 0.5454545454545454,
7598
+ "mmlu_eval_accuracy_college_mathematics": 0.2727272727272727,
7599
+ "mmlu_eval_accuracy_college_medicine": 0.5,
7600
+ "mmlu_eval_accuracy_college_physics": 0.5454545454545454,
7601
+ "mmlu_eval_accuracy_computer_security": 0.45454545454545453,
7602
+ "mmlu_eval_accuracy_conceptual_physics": 0.46153846153846156,
7603
+ "mmlu_eval_accuracy_econometrics": 0.25,
7604
+ "mmlu_eval_accuracy_electrical_engineering": 0.375,
7605
+ "mmlu_eval_accuracy_elementary_mathematics": 0.36585365853658536,
7606
+ "mmlu_eval_accuracy_formal_logic": 0.14285714285714285,
7607
+ "mmlu_eval_accuracy_global_facts": 0.3,
7608
+ "mmlu_eval_accuracy_high_school_biology": 0.5,
7609
+ "mmlu_eval_accuracy_high_school_chemistry": 0.4090909090909091,
7610
+ "mmlu_eval_accuracy_high_school_computer_science": 0.6666666666666666,
7611
+ "mmlu_eval_accuracy_high_school_european_history": 0.6666666666666666,
7612
+ "mmlu_eval_accuracy_high_school_geography": 0.9090909090909091,
7613
+ "mmlu_eval_accuracy_high_school_government_and_politics": 0.5714285714285714,
7614
+ "mmlu_eval_accuracy_high_school_macroeconomics": 0.37209302325581395,
7615
+ "mmlu_eval_accuracy_high_school_mathematics": 0.20689655172413793,
7616
+ "mmlu_eval_accuracy_high_school_microeconomics": 0.46153846153846156,
7617
+ "mmlu_eval_accuracy_high_school_physics": 0.11764705882352941,
7618
+ "mmlu_eval_accuracy_high_school_psychology": 0.8333333333333334,
7619
+ "mmlu_eval_accuracy_high_school_statistics": 0.4782608695652174,
7620
+ "mmlu_eval_accuracy_high_school_us_history": 0.7727272727272727,
7621
+ "mmlu_eval_accuracy_high_school_world_history": 0.6538461538461539,
7622
+ "mmlu_eval_accuracy_human_aging": 0.6956521739130435,
7623
+ "mmlu_eval_accuracy_human_sexuality": 0.5,
7624
+ "mmlu_eval_accuracy_international_law": 0.8461538461538461,
7625
+ "mmlu_eval_accuracy_jurisprudence": 0.36363636363636365,
7626
+ "mmlu_eval_accuracy_logical_fallacies": 0.6666666666666666,
7627
+ "mmlu_eval_accuracy_machine_learning": 0.18181818181818182,
7628
+ "mmlu_eval_accuracy_management": 0.7272727272727273,
7629
+ "mmlu_eval_accuracy_marketing": 0.8,
7630
+ "mmlu_eval_accuracy_medical_genetics": 0.8181818181818182,
7631
+ "mmlu_eval_accuracy_miscellaneous": 0.6395348837209303,
7632
+ "mmlu_eval_accuracy_moral_disputes": 0.4473684210526316,
7633
+ "mmlu_eval_accuracy_moral_scenarios": 0.23,
7634
+ "mmlu_eval_accuracy_nutrition": 0.6666666666666666,
7635
+ "mmlu_eval_accuracy_philosophy": 0.5294117647058824,
7636
+ "mmlu_eval_accuracy_prehistory": 0.45714285714285713,
7637
+ "mmlu_eval_accuracy_professional_accounting": 0.25806451612903225,
7638
+ "mmlu_eval_accuracy_professional_law": 0.3411764705882353,
7639
+ "mmlu_eval_accuracy_professional_medicine": 0.5161290322580645,
7640
+ "mmlu_eval_accuracy_professional_psychology": 0.4492753623188406,
7641
+ "mmlu_eval_accuracy_public_relations": 0.4166666666666667,
7642
+ "mmlu_eval_accuracy_security_studies": 0.5555555555555556,
7643
+ "mmlu_eval_accuracy_sociology": 0.8181818181818182,
7644
+ "mmlu_eval_accuracy_us_foreign_policy": 0.7272727272727273,
7645
+ "mmlu_eval_accuracy_virology": 0.4444444444444444,
7646
+ "mmlu_eval_accuracy_world_religions": 0.7894736842105263,
7647
+ "mmlu_loss": 1.4539437902113788,
7648
+ "step": 8000
7649
+ },
7650
+ {
7651
+ "epoch": 3.63,
7652
+ "learning_rate": 0.0002,
7653
+ "loss": 0.6682,
7654
+ "step": 8010
7655
+ },
7656
+ {
7657
+ "epoch": 3.63,
7658
+ "learning_rate": 0.0002,
7659
+ "loss": 0.7483,
7660
+ "step": 8020
7661
+ },
7662
+ {
7663
+ "epoch": 3.64,
7664
+ "learning_rate": 0.0002,
7665
+ "loss": 0.697,
7666
+ "step": 8030
7667
+ },
7668
+ {
7669
+ "epoch": 3.64,
7670
+ "learning_rate": 0.0002,
7671
+ "loss": 0.7493,
7672
+ "step": 8040
7673
+ },
7674
+ {
7675
+ "epoch": 3.64,
7676
+ "learning_rate": 0.0002,
7677
+ "loss": 0.8147,
7678
+ "step": 8050
7679
+ },
7680
+ {
7681
+ "epoch": 3.65,
7682
+ "learning_rate": 0.0002,
7683
+ "loss": 0.7484,
7684
+ "step": 8060
7685
+ },
7686
+ {
7687
+ "epoch": 3.65,
7688
+ "learning_rate": 0.0002,
7689
+ "loss": 0.7828,
7690
+ "step": 8070
7691
+ },
7692
+ {
7693
+ "epoch": 3.66,
7694
+ "learning_rate": 0.0002,
7695
+ "loss": 0.6756,
7696
+ "step": 8080
7697
+ },
7698
+ {
7699
+ "epoch": 3.66,
7700
+ "learning_rate": 0.0002,
7701
+ "loss": 0.8711,
7702
+ "step": 8090
7703
+ },
7704
+ {
7705
+ "epoch": 3.67,
7706
+ "learning_rate": 0.0002,
7707
+ "loss": 0.7307,
7708
+ "step": 8100
7709
+ },
7710
+ {
7711
+ "epoch": 3.67,
7712
+ "learning_rate": 0.0002,
7713
+ "loss": 0.7542,
7714
+ "step": 8110
7715
+ },
7716
+ {
7717
+ "epoch": 3.68,
7718
+ "learning_rate": 0.0002,
7719
+ "loss": 0.722,
7720
+ "step": 8120
7721
+ },
7722
+ {
7723
+ "epoch": 3.68,
7724
+ "learning_rate": 0.0002,
7725
+ "loss": 0.7708,
7726
+ "step": 8130
7727
+ },
7728
+ {
7729
+ "epoch": 3.68,
7730
+ "learning_rate": 0.0002,
7731
+ "loss": 0.6998,
7732
+ "step": 8140
7733
+ },
7734
+ {
7735
+ "epoch": 3.69,
7736
+ "learning_rate": 0.0002,
7737
+ "loss": 0.7725,
7738
+ "step": 8150
7739
+ },
7740
+ {
7741
+ "epoch": 3.69,
7742
+ "learning_rate": 0.0002,
7743
+ "loss": 0.765,
7744
+ "step": 8160
7745
+ },
7746
+ {
7747
+ "epoch": 3.7,
7748
+ "learning_rate": 0.0002,
7749
+ "loss": 0.7523,
7750
+ "step": 8170
7751
+ },
7752
+ {
7753
+ "epoch": 3.7,
7754
+ "learning_rate": 0.0002,
7755
+ "loss": 0.7689,
7756
+ "step": 8180
7757
+ },
7758
+ {
7759
+ "epoch": 3.71,
7760
+ "learning_rate": 0.0002,
7761
+ "loss": 0.7549,
7762
+ "step": 8190
7763
+ },
7764
+ {
7765
+ "epoch": 3.71,
7766
+ "learning_rate": 0.0002,
7767
+ "loss": 0.7585,
7768
+ "step": 8200
7769
+ },
7770
+ {
7771
+ "epoch": 3.71,
7772
+ "eval_loss": 1.0938563346862793,
7773
+ "eval_runtime": 130.749,
7774
+ "eval_samples_per_second": 7.648,
7775
+ "eval_steps_per_second": 3.824,
7776
+ "step": 8200
7777
+ },
7778
+ {
7779
+ "epoch": 3.71,
7780
+ "mmlu_eval_accuracy": 0.509832805467066,
7781
+ "mmlu_eval_accuracy_abstract_algebra": 0.18181818181818182,
7782
+ "mmlu_eval_accuracy_anatomy": 0.5714285714285714,
7783
+ "mmlu_eval_accuracy_astronomy": 0.5,
7784
+ "mmlu_eval_accuracy_business_ethics": 0.45454545454545453,
7785
+ "mmlu_eval_accuracy_clinical_knowledge": 0.5862068965517241,
7786
+ "mmlu_eval_accuracy_college_biology": 0.3125,
7787
+ "mmlu_eval_accuracy_college_chemistry": 0.625,
7788
+ "mmlu_eval_accuracy_college_computer_science": 0.45454545454545453,
7789
+ "mmlu_eval_accuracy_college_mathematics": 0.2727272727272727,
7790
+ "mmlu_eval_accuracy_college_medicine": 0.5,
7791
+ "mmlu_eval_accuracy_college_physics": 0.45454545454545453,
7792
+ "mmlu_eval_accuracy_computer_security": 0.36363636363636365,
7793
+ "mmlu_eval_accuracy_conceptual_physics": 0.4230769230769231,
7794
+ "mmlu_eval_accuracy_econometrics": 0.16666666666666666,
7795
+ "mmlu_eval_accuracy_electrical_engineering": 0.375,
7796
+ "mmlu_eval_accuracy_elementary_mathematics": 0.3902439024390244,
7797
+ "mmlu_eval_accuracy_formal_logic": 0.14285714285714285,
7798
+ "mmlu_eval_accuracy_global_facts": 0.3,
7799
+ "mmlu_eval_accuracy_high_school_biology": 0.46875,
7800
+ "mmlu_eval_accuracy_high_school_chemistry": 0.45454545454545453,
7801
+ "mmlu_eval_accuracy_high_school_computer_science": 0.6666666666666666,
7802
+ "mmlu_eval_accuracy_high_school_european_history": 0.7222222222222222,
7803
+ "mmlu_eval_accuracy_high_school_geography": 0.9090909090909091,
7804
+ "mmlu_eval_accuracy_high_school_government_and_politics": 0.5714285714285714,
7805
+ "mmlu_eval_accuracy_high_school_macroeconomics": 0.4186046511627907,
7806
+ "mmlu_eval_accuracy_high_school_mathematics": 0.27586206896551724,
7807
+ "mmlu_eval_accuracy_high_school_microeconomics": 0.46153846153846156,
7808
+ "mmlu_eval_accuracy_high_school_physics": 0.11764705882352941,
7809
+ "mmlu_eval_accuracy_high_school_psychology": 0.85,
7810
+ "mmlu_eval_accuracy_high_school_statistics": 0.4782608695652174,
7811
+ "mmlu_eval_accuracy_high_school_us_history": 0.7272727272727273,
7812
+ "mmlu_eval_accuracy_high_school_world_history": 0.6538461538461539,
7813
+ "mmlu_eval_accuracy_human_aging": 0.7391304347826086,
7814
+ "mmlu_eval_accuracy_human_sexuality": 0.5,
7815
+ "mmlu_eval_accuracy_international_law": 0.8461538461538461,
7816
+ "mmlu_eval_accuracy_jurisprudence": 0.45454545454545453,
7817
+ "mmlu_eval_accuracy_logical_fallacies": 0.6111111111111112,
7818
+ "mmlu_eval_accuracy_machine_learning": 0.2727272727272727,
7819
+ "mmlu_eval_accuracy_management": 0.8181818181818182,
7820
+ "mmlu_eval_accuracy_marketing": 0.8,
7821
+ "mmlu_eval_accuracy_medical_genetics": 0.7272727272727273,
7822
+ "mmlu_eval_accuracy_miscellaneous": 0.6744186046511628,
7823
+ "mmlu_eval_accuracy_moral_disputes": 0.5,
7824
+ "mmlu_eval_accuracy_moral_scenarios": 0.25,
7825
+ "mmlu_eval_accuracy_nutrition": 0.6666666666666666,
7826
+ "mmlu_eval_accuracy_philosophy": 0.5,
7827
+ "mmlu_eval_accuracy_prehistory": 0.42857142857142855,
7828
+ "mmlu_eval_accuracy_professional_accounting": 0.25806451612903225,
7829
+ "mmlu_eval_accuracy_professional_law": 0.34705882352941175,
7830
+ "mmlu_eval_accuracy_professional_medicine": 0.5161290322580645,
7831
+ "mmlu_eval_accuracy_professional_psychology": 0.4927536231884058,
7832
+ "mmlu_eval_accuracy_public_relations": 0.4166666666666667,
7833
+ "mmlu_eval_accuracy_security_studies": 0.5555555555555556,
7834
+ "mmlu_eval_accuracy_sociology": 0.8181818181818182,
7835
+ "mmlu_eval_accuracy_us_foreign_policy": 0.7272727272727273,
7836
+ "mmlu_eval_accuracy_virology": 0.5,
7837
+ "mmlu_eval_accuracy_world_religions": 0.7894736842105263,
7838
+ "mmlu_loss": 1.2966852889398681,
7839
+ "step": 8200
7840
+ },
7841
+ {
7842
+ "epoch": 3.72,
7843
+ "learning_rate": 0.0002,
7844
+ "loss": 0.757,
7845
+ "step": 8210
7846
+ },
7847
+ {
7848
+ "epoch": 3.72,
7849
+ "learning_rate": 0.0002,
7850
+ "loss": 0.7398,
7851
+ "step": 8220
7852
+ },
7853
+ {
7854
+ "epoch": 3.73,
7855
+ "learning_rate": 0.0002,
7856
+ "loss": 0.7923,
7857
+ "step": 8230
7858
+ },
7859
+ {
7860
+ "epoch": 3.73,
7861
+ "learning_rate": 0.0002,
7862
+ "loss": 0.7271,
7863
+ "step": 8240
7864
+ },
7865
+ {
7866
+ "epoch": 3.73,
7867
+ "learning_rate": 0.0002,
7868
+ "loss": 0.7932,
7869
+ "step": 8250
7870
+ },
7871
+ {
7872
+ "epoch": 3.74,
7873
+ "learning_rate": 0.0002,
7874
+ "loss": 0.7686,
7875
+ "step": 8260
7876
+ },
7877
+ {
7878
+ "epoch": 3.74,
7879
+ "learning_rate": 0.0002,
7880
+ "loss": 0.6725,
7881
+ "step": 8270
7882
+ },
7883
+ {
7884
+ "epoch": 3.75,
7885
+ "learning_rate": 0.0002,
7886
+ "loss": 0.7114,
7887
+ "step": 8280
7888
+ },
7889
+ {
7890
+ "epoch": 3.75,
7891
+ "learning_rate": 0.0002,
7892
+ "loss": 0.7855,
7893
+ "step": 8290
7894
+ },
7895
+ {
7896
+ "epoch": 3.76,
7897
+ "learning_rate": 0.0002,
7898
+ "loss": 0.7489,
7899
+ "step": 8300
7900
+ },
7901
+ {
7902
+ "epoch": 3.76,
7903
+ "learning_rate": 0.0002,
7904
+ "loss": 0.7611,
7905
+ "step": 8310
7906
+ },
7907
+ {
7908
+ "epoch": 3.77,
7909
+ "learning_rate": 0.0002,
7910
+ "loss": 0.7051,
7911
+ "step": 8320
7912
+ },
7913
+ {
7914
+ "epoch": 3.77,
7915
+ "learning_rate": 0.0002,
7916
+ "loss": 0.7394,
7917
+ "step": 8330
7918
+ },
7919
+ {
7920
+ "epoch": 3.78,
7921
+ "learning_rate": 0.0002,
7922
+ "loss": 0.7712,
7923
+ "step": 8340
7924
+ },
7925
+ {
7926
+ "epoch": 3.78,
7927
+ "learning_rate": 0.0002,
7928
+ "loss": 0.745,
7929
+ "step": 8350
7930
+ },
7931
+ {
7932
+ "epoch": 3.78,
7933
+ "learning_rate": 0.0002,
7934
+ "loss": 0.6815,
7935
+ "step": 8360
7936
+ },
7937
+ {
7938
+ "epoch": 3.79,
7939
+ "learning_rate": 0.0002,
7940
+ "loss": 0.6954,
7941
+ "step": 8370
7942
+ },
7943
+ {
7944
+ "epoch": 3.79,
7945
+ "learning_rate": 0.0002,
7946
+ "loss": 0.6684,
7947
+ "step": 8380
7948
+ },
7949
+ {
7950
+ "epoch": 3.8,
7951
+ "learning_rate": 0.0002,
7952
+ "loss": 0.7217,
7953
+ "step": 8390
7954
+ },
7955
+ {
7956
+ "epoch": 3.8,
7957
+ "learning_rate": 0.0002,
7958
+ "loss": 0.7681,
7959
+ "step": 8400
7960
+ },
7961
+ {
7962
+ "epoch": 3.8,
7963
+ "eval_loss": 1.101223111152649,
7964
+ "eval_runtime": 131.7525,
7965
+ "eval_samples_per_second": 7.59,
7966
+ "eval_steps_per_second": 3.795,
7967
+ "step": 8400
7968
+ },
7969
+ {
7970
+ "epoch": 3.8,
7971
+ "mmlu_eval_accuracy": 0.5146294321294028,
7972
+ "mmlu_eval_accuracy_abstract_algebra": 0.18181818181818182,
7973
+ "mmlu_eval_accuracy_anatomy": 0.5,
7974
+ "mmlu_eval_accuracy_astronomy": 0.5,
7975
+ "mmlu_eval_accuracy_business_ethics": 0.45454545454545453,
7976
+ "mmlu_eval_accuracy_clinical_knowledge": 0.5517241379310345,
7977
+ "mmlu_eval_accuracy_college_biology": 0.4375,
7978
+ "mmlu_eval_accuracy_college_chemistry": 0.625,
7979
+ "mmlu_eval_accuracy_college_computer_science": 0.45454545454545453,
7980
+ "mmlu_eval_accuracy_college_mathematics": 0.18181818181818182,
7981
+ "mmlu_eval_accuracy_college_medicine": 0.5454545454545454,
7982
+ "mmlu_eval_accuracy_college_physics": 0.5454545454545454,
7983
+ "mmlu_eval_accuracy_computer_security": 0.36363636363636365,
7984
+ "mmlu_eval_accuracy_conceptual_physics": 0.5,
7985
+ "mmlu_eval_accuracy_econometrics": 0.25,
7986
+ "mmlu_eval_accuracy_electrical_engineering": 0.375,
7987
+ "mmlu_eval_accuracy_elementary_mathematics": 0.3170731707317073,
7988
+ "mmlu_eval_accuracy_formal_logic": 0.21428571428571427,
7989
+ "mmlu_eval_accuracy_global_facts": 0.4,
7990
+ "mmlu_eval_accuracy_high_school_biology": 0.5,
7991
+ "mmlu_eval_accuracy_high_school_chemistry": 0.5,
7992
+ "mmlu_eval_accuracy_high_school_computer_science": 0.6666666666666666,
7993
+ "mmlu_eval_accuracy_high_school_european_history": 0.7222222222222222,
7994
+ "mmlu_eval_accuracy_high_school_geography": 0.9090909090909091,
7995
+ "mmlu_eval_accuracy_high_school_government_and_politics": 0.5714285714285714,
7996
+ "mmlu_eval_accuracy_high_school_macroeconomics": 0.4418604651162791,
7997
+ "mmlu_eval_accuracy_high_school_mathematics": 0.2413793103448276,
7998
+ "mmlu_eval_accuracy_high_school_microeconomics": 0.5769230769230769,
7999
+ "mmlu_eval_accuracy_high_school_physics": 0.17647058823529413,
8000
+ "mmlu_eval_accuracy_high_school_psychology": 0.8666666666666667,
8001
+ "mmlu_eval_accuracy_high_school_statistics": 0.43478260869565216,
8002
+ "mmlu_eval_accuracy_high_school_us_history": 0.7727272727272727,
8003
+ "mmlu_eval_accuracy_high_school_world_history": 0.6538461538461539,
8004
+ "mmlu_eval_accuracy_human_aging": 0.6086956521739131,
8005
+ "mmlu_eval_accuracy_human_sexuality": 0.5,
8006
+ "mmlu_eval_accuracy_international_law": 0.8461538461538461,
8007
+ "mmlu_eval_accuracy_jurisprudence": 0.45454545454545453,
8008
+ "mmlu_eval_accuracy_logical_fallacies": 0.6666666666666666,
8009
+ "mmlu_eval_accuracy_machine_learning": 0.2727272727272727,
8010
+ "mmlu_eval_accuracy_management": 0.7272727272727273,
8011
+ "mmlu_eval_accuracy_marketing": 0.84,
8012
+ "mmlu_eval_accuracy_medical_genetics": 0.8181818181818182,
8013
+ "mmlu_eval_accuracy_miscellaneous": 0.627906976744186,
8014
+ "mmlu_eval_accuracy_moral_disputes": 0.5,
8015
+ "mmlu_eval_accuracy_moral_scenarios": 0.23,
8016
+ "mmlu_eval_accuracy_nutrition": 0.6666666666666666,
8017
+ "mmlu_eval_accuracy_philosophy": 0.5294117647058824,
8018
+ "mmlu_eval_accuracy_prehistory": 0.42857142857142855,
8019
+ "mmlu_eval_accuracy_professional_accounting": 0.16129032258064516,
8020
+ "mmlu_eval_accuracy_professional_law": 0.32941176470588235,
8021
+ "mmlu_eval_accuracy_professional_medicine": 0.5161290322580645,
8022
+ "mmlu_eval_accuracy_professional_psychology": 0.463768115942029,
8023
+ "mmlu_eval_accuracy_public_relations": 0.4166666666666667,
8024
+ "mmlu_eval_accuracy_security_studies": 0.5185185185185185,
8025
+ "mmlu_eval_accuracy_sociology": 0.8181818181818182,
8026
+ "mmlu_eval_accuracy_us_foreign_policy": 0.7272727272727273,
8027
+ "mmlu_eval_accuracy_virology": 0.4444444444444444,
8028
+ "mmlu_eval_accuracy_world_religions": 0.7894736842105263,
8029
+ "mmlu_loss": 1.40192161761127,
8030
+ "step": 8400
8031
+ },
8032
+ {
8033
+ "epoch": 3.81,
8034
+ "learning_rate": 0.0002,
8035
+ "loss": 0.7766,
8036
+ "step": 8410
8037
+ },
8038
+ {
8039
+ "epoch": 3.81,
8040
+ "learning_rate": 0.0002,
8041
+ "loss": 0.6984,
8042
+ "step": 8420
8043
+ },
8044
+ {
8045
+ "epoch": 3.82,
8046
+ "learning_rate": 0.0002,
8047
+ "loss": 0.7283,
8048
+ "step": 8430
8049
+ },
8050
+ {
8051
+ "epoch": 3.82,
8052
+ "learning_rate": 0.0002,
8053
+ "loss": 0.7122,
8054
+ "step": 8440
8055
+ },
8056
+ {
8057
+ "epoch": 3.83,
8058
+ "learning_rate": 0.0002,
8059
+ "loss": 0.7026,
8060
+ "step": 8450
8061
+ },
8062
+ {
8063
+ "epoch": 3.83,
8064
+ "learning_rate": 0.0002,
8065
+ "loss": 0.7262,
8066
+ "step": 8460
8067
+ },
8068
+ {
8069
+ "epoch": 3.83,
8070
+ "learning_rate": 0.0002,
8071
+ "loss": 0.692,
8072
+ "step": 8470
8073
+ },
8074
+ {
8075
+ "epoch": 3.84,
8076
+ "learning_rate": 0.0002,
8077
+ "loss": 0.7611,
8078
+ "step": 8480
8079
+ },
8080
+ {
8081
+ "epoch": 3.84,
8082
+ "learning_rate": 0.0002,
8083
+ "loss": 0.7602,
8084
+ "step": 8490
8085
+ },
8086
+ {
8087
+ "epoch": 3.85,
8088
+ "learning_rate": 0.0002,
8089
+ "loss": 0.728,
8090
+ "step": 8500
8091
+ },
8092
+ {
8093
+ "epoch": 3.85,
8094
+ "learning_rate": 0.0002,
8095
+ "loss": 0.6521,
8096
+ "step": 8510
8097
+ },
8098
+ {
8099
+ "epoch": 3.86,
8100
+ "learning_rate": 0.0002,
8101
+ "loss": 0.7307,
8102
+ "step": 8520
8103
+ },
8104
+ {
8105
+ "epoch": 3.86,
8106
+ "learning_rate": 0.0002,
8107
+ "loss": 0.706,
8108
+ "step": 8530
8109
+ },
8110
+ {
8111
+ "epoch": 3.87,
8112
+ "learning_rate": 0.0002,
8113
+ "loss": 0.7543,
8114
+ "step": 8540
8115
+ },
8116
+ {
8117
+ "epoch": 3.87,
8118
+ "learning_rate": 0.0002,
8119
+ "loss": 0.7194,
8120
+ "step": 8550
8121
+ },
8122
+ {
8123
+ "epoch": 3.88,
8124
+ "learning_rate": 0.0002,
8125
+ "loss": 0.7664,
8126
+ "step": 8560
8127
+ },
8128
+ {
8129
+ "epoch": 3.88,
8130
+ "learning_rate": 0.0002,
8131
+ "loss": 0.7834,
8132
+ "step": 8570
8133
+ },
8134
+ {
8135
+ "epoch": 3.88,
8136
+ "learning_rate": 0.0002,
8137
+ "loss": 0.7056,
8138
+ "step": 8580
8139
+ },
8140
+ {
8141
+ "epoch": 3.89,
8142
+ "learning_rate": 0.0002,
8143
+ "loss": 0.7865,
8144
+ "step": 8590
8145
+ },
8146
+ {
8147
+ "epoch": 3.89,
8148
+ "learning_rate": 0.0002,
8149
+ "loss": 0.7447,
8150
+ "step": 8600
8151
+ },
8152
+ {
8153
+ "epoch": 3.89,
8154
+ "eval_loss": 1.0886354446411133,
8155
+ "eval_runtime": 131.9847,
8156
+ "eval_samples_per_second": 7.577,
8157
+ "eval_steps_per_second": 3.788,
8158
+ "step": 8600
8159
+ },
8160
+ {
8161
+ "epoch": 3.89,
8162
+ "mmlu_eval_accuracy": 0.5103698915592155,
8163
+ "mmlu_eval_accuracy_abstract_algebra": 0.2727272727272727,
8164
+ "mmlu_eval_accuracy_anatomy": 0.5,
8165
+ "mmlu_eval_accuracy_astronomy": 0.5,
8166
+ "mmlu_eval_accuracy_business_ethics": 0.45454545454545453,
8167
+ "mmlu_eval_accuracy_clinical_knowledge": 0.4827586206896552,
8168
+ "mmlu_eval_accuracy_college_biology": 0.3125,
8169
+ "mmlu_eval_accuracy_college_chemistry": 0.5,
8170
+ "mmlu_eval_accuracy_college_computer_science": 0.45454545454545453,
8171
+ "mmlu_eval_accuracy_college_mathematics": 0.18181818181818182,
8172
+ "mmlu_eval_accuracy_college_medicine": 0.5,
8173
+ "mmlu_eval_accuracy_college_physics": 0.45454545454545453,
8174
+ "mmlu_eval_accuracy_computer_security": 0.45454545454545453,
8175
+ "mmlu_eval_accuracy_conceptual_physics": 0.46153846153846156,
8176
+ "mmlu_eval_accuracy_econometrics": 0.25,
8177
+ "mmlu_eval_accuracy_electrical_engineering": 0.4375,
8178
+ "mmlu_eval_accuracy_elementary_mathematics": 0.34146341463414637,
8179
+ "mmlu_eval_accuracy_formal_logic": 0.14285714285714285,
8180
+ "mmlu_eval_accuracy_global_facts": 0.4,
8181
+ "mmlu_eval_accuracy_high_school_biology": 0.5,
8182
+ "mmlu_eval_accuracy_high_school_chemistry": 0.5,
8183
+ "mmlu_eval_accuracy_high_school_computer_science": 0.6666666666666666,
8184
+ "mmlu_eval_accuracy_high_school_european_history": 0.6666666666666666,
8185
+ "mmlu_eval_accuracy_high_school_geography": 0.9090909090909091,
8186
+ "mmlu_eval_accuracy_high_school_government_and_politics": 0.6190476190476191,
8187
+ "mmlu_eval_accuracy_high_school_macroeconomics": 0.4186046511627907,
8188
+ "mmlu_eval_accuracy_high_school_mathematics": 0.2413793103448276,
8189
+ "mmlu_eval_accuracy_high_school_microeconomics": 0.5769230769230769,
8190
+ "mmlu_eval_accuracy_high_school_physics": 0.23529411764705882,
8191
+ "mmlu_eval_accuracy_high_school_psychology": 0.8666666666666667,
8192
+ "mmlu_eval_accuracy_high_school_statistics": 0.4782608695652174,
8193
+ "mmlu_eval_accuracy_high_school_us_history": 0.7727272727272727,
8194
+ "mmlu_eval_accuracy_high_school_world_history": 0.6923076923076923,
8195
+ "mmlu_eval_accuracy_human_aging": 0.6521739130434783,
8196
+ "mmlu_eval_accuracy_human_sexuality": 0.5,
8197
+ "mmlu_eval_accuracy_international_law": 0.8461538461538461,
8198
+ "mmlu_eval_accuracy_jurisprudence": 0.45454545454545453,
8199
+ "mmlu_eval_accuracy_logical_fallacies": 0.6111111111111112,
8200
+ "mmlu_eval_accuracy_machine_learning": 0.18181818181818182,
8201
+ "mmlu_eval_accuracy_management": 0.8181818181818182,
8202
+ "mmlu_eval_accuracy_marketing": 0.8,
8203
+ "mmlu_eval_accuracy_medical_genetics": 0.7272727272727273,
8204
+ "mmlu_eval_accuracy_miscellaneous": 0.6511627906976745,
8205
+ "mmlu_eval_accuracy_moral_disputes": 0.5,
8206
+ "mmlu_eval_accuracy_moral_scenarios": 0.23,
8207
+ "mmlu_eval_accuracy_nutrition": 0.6363636363636364,
8208
+ "mmlu_eval_accuracy_philosophy": 0.5588235294117647,
8209
+ "mmlu_eval_accuracy_prehistory": 0.42857142857142855,
8210
+ "mmlu_eval_accuracy_professional_accounting": 0.25806451612903225,
8211
+ "mmlu_eval_accuracy_professional_law": 0.3411764705882353,
8212
+ "mmlu_eval_accuracy_professional_medicine": 0.5161290322580645,
8213
+ "mmlu_eval_accuracy_professional_psychology": 0.463768115942029,
8214
+ "mmlu_eval_accuracy_public_relations": 0.4166666666666667,
8215
+ "mmlu_eval_accuracy_security_studies": 0.5555555555555556,
8216
+ "mmlu_eval_accuracy_sociology": 0.6818181818181818,
8217
+ "mmlu_eval_accuracy_us_foreign_policy": 0.7272727272727273,
8218
+ "mmlu_eval_accuracy_virology": 0.5,
8219
+ "mmlu_eval_accuracy_world_religions": 0.7894736842105263,
8220
+ "mmlu_loss": 1.1779243290307628,
8221
+ "step": 8600
8222
+ },
8223
+ {
8224
+ "epoch": 3.9,
8225
+ "learning_rate": 0.0002,
8226
+ "loss": 0.7995,
8227
+ "step": 8610
8228
+ },
8229
+ {
8230
+ "epoch": 3.9,
8231
+ "learning_rate": 0.0002,
8232
+ "loss": 0.7566,
8233
+ "step": 8620
8234
+ },
8235
+ {
8236
+ "epoch": 3.91,
8237
+ "learning_rate": 0.0002,
8238
+ "loss": 0.7641,
8239
+ "step": 8630
8240
+ },
8241
+ {
8242
+ "epoch": 3.91,
8243
+ "learning_rate": 0.0002,
8244
+ "loss": 0.6799,
8245
+ "step": 8640
8246
+ },
8247
+ {
8248
+ "epoch": 3.92,
8249
+ "learning_rate": 0.0002,
8250
+ "loss": 0.818,
8251
+ "step": 8650
8252
+ },
8253
+ {
8254
+ "epoch": 3.92,
8255
+ "learning_rate": 0.0002,
8256
+ "loss": 0.8231,
8257
+ "step": 8660
8258
+ },
8259
+ {
8260
+ "epoch": 3.92,
8261
+ "learning_rate": 0.0002,
8262
+ "loss": 0.7193,
8263
+ "step": 8670
8264
+ },
8265
+ {
8266
+ "epoch": 3.93,
8267
+ "learning_rate": 0.0002,
8268
+ "loss": 0.7682,
8269
+ "step": 8680
8270
+ },
8271
+ {
8272
+ "epoch": 3.93,
8273
+ "learning_rate": 0.0002,
8274
+ "loss": 0.7347,
8275
+ "step": 8690
8276
+ },
8277
+ {
8278
+ "epoch": 3.94,
8279
+ "learning_rate": 0.0002,
8280
+ "loss": 0.7126,
8281
+ "step": 8700
8282
+ },
8283
+ {
8284
+ "epoch": 3.94,
8285
+ "learning_rate": 0.0002,
8286
+ "loss": 0.6826,
8287
+ "step": 8710
8288
+ },
8289
+ {
8290
+ "epoch": 3.95,
8291
+ "learning_rate": 0.0002,
8292
+ "loss": 0.7224,
8293
+ "step": 8720
8294
+ },
8295
+ {
8296
+ "epoch": 3.95,
8297
+ "learning_rate": 0.0002,
8298
+ "loss": 0.7735,
8299
+ "step": 8730
8300
+ },
8301
+ {
8302
+ "epoch": 3.96,
8303
+ "learning_rate": 0.0002,
8304
+ "loss": 0.6892,
8305
+ "step": 8740
8306
+ },
8307
+ {
8308
+ "epoch": 3.96,
8309
+ "learning_rate": 0.0002,
8310
+ "loss": 0.7329,
8311
+ "step": 8750
8312
+ },
8313
+ {
8314
+ "epoch": 3.97,
8315
+ "learning_rate": 0.0002,
8316
+ "loss": 0.728,
8317
+ "step": 8760
8318
+ },
8319
+ {
8320
+ "epoch": 3.97,
8321
+ "learning_rate": 0.0002,
8322
+ "loss": 0.726,
8323
+ "step": 8770
8324
+ },
8325
+ {
8326
+ "epoch": 3.97,
8327
+ "learning_rate": 0.0002,
8328
+ "loss": 0.7793,
8329
+ "step": 8780
8330
+ },
8331
+ {
8332
+ "epoch": 3.98,
8333
+ "learning_rate": 0.0002,
8334
+ "loss": 0.7559,
8335
+ "step": 8790
8336
+ },
8337
+ {
8338
+ "epoch": 3.98,
8339
+ "learning_rate": 0.0002,
8340
+ "loss": 0.7568,
8341
+ "step": 8800
8342
+ },
8343
+ {
8344
+ "epoch": 3.98,
8345
+ "eval_loss": 1.0907299518585205,
8346
+ "eval_runtime": 131.9363,
8347
+ "eval_samples_per_second": 7.579,
8348
+ "eval_steps_per_second": 3.79,
8349
+ "step": 8800
8350
+ },
8351
+ {
8352
+ "epoch": 3.98,
8353
+ "mmlu_eval_accuracy": 0.5111124912693479,
8354
+ "mmlu_eval_accuracy_abstract_algebra": 0.2727272727272727,
8355
+ "mmlu_eval_accuracy_anatomy": 0.6428571428571429,
8356
+ "mmlu_eval_accuracy_astronomy": 0.5,
8357
+ "mmlu_eval_accuracy_business_ethics": 0.45454545454545453,
8358
+ "mmlu_eval_accuracy_clinical_knowledge": 0.5172413793103449,
8359
+ "mmlu_eval_accuracy_college_biology": 0.5,
8360
+ "mmlu_eval_accuracy_college_chemistry": 0.5,
8361
+ "mmlu_eval_accuracy_college_computer_science": 0.45454545454545453,
8362
+ "mmlu_eval_accuracy_college_mathematics": 0.18181818181818182,
8363
+ "mmlu_eval_accuracy_college_medicine": 0.45454545454545453,
8364
+ "mmlu_eval_accuracy_college_physics": 0.45454545454545453,
8365
+ "mmlu_eval_accuracy_computer_security": 0.36363636363636365,
8366
+ "mmlu_eval_accuracy_conceptual_physics": 0.5,
8367
+ "mmlu_eval_accuracy_econometrics": 0.16666666666666666,
8368
+ "mmlu_eval_accuracy_electrical_engineering": 0.4375,
8369
+ "mmlu_eval_accuracy_elementary_mathematics": 0.2926829268292683,
8370
+ "mmlu_eval_accuracy_formal_logic": 0.14285714285714285,
8371
+ "mmlu_eval_accuracy_global_facts": 0.4,
8372
+ "mmlu_eval_accuracy_high_school_biology": 0.53125,
8373
+ "mmlu_eval_accuracy_high_school_chemistry": 0.5,
8374
+ "mmlu_eval_accuracy_high_school_computer_science": 0.5555555555555556,
8375
+ "mmlu_eval_accuracy_high_school_european_history": 0.6666666666666666,
8376
+ "mmlu_eval_accuracy_high_school_geography": 0.9090909090909091,
8377
+ "mmlu_eval_accuracy_high_school_government_and_politics": 0.6190476190476191,
8378
+ "mmlu_eval_accuracy_high_school_macroeconomics": 0.4418604651162791,
8379
+ "mmlu_eval_accuracy_high_school_mathematics": 0.27586206896551724,
8380
+ "mmlu_eval_accuracy_high_school_microeconomics": 0.5384615384615384,
8381
+ "mmlu_eval_accuracy_high_school_physics": 0.23529411764705882,
8382
+ "mmlu_eval_accuracy_high_school_psychology": 0.85,
8383
+ "mmlu_eval_accuracy_high_school_statistics": 0.5217391304347826,
8384
+ "mmlu_eval_accuracy_high_school_us_history": 0.7727272727272727,
8385
+ "mmlu_eval_accuracy_high_school_world_history": 0.6538461538461539,
8386
+ "mmlu_eval_accuracy_human_aging": 0.6521739130434783,
8387
+ "mmlu_eval_accuracy_human_sexuality": 0.5,
8388
+ "mmlu_eval_accuracy_international_law": 0.8461538461538461,
8389
+ "mmlu_eval_accuracy_jurisprudence": 0.5454545454545454,
8390
+ "mmlu_eval_accuracy_logical_fallacies": 0.6111111111111112,
8391
+ "mmlu_eval_accuracy_machine_learning": 0.18181818181818182,
8392
+ "mmlu_eval_accuracy_management": 0.7272727272727273,
8393
+ "mmlu_eval_accuracy_marketing": 0.8,
8394
+ "mmlu_eval_accuracy_medical_genetics": 0.7272727272727273,
8395
+ "mmlu_eval_accuracy_miscellaneous": 0.6162790697674418,
8396
+ "mmlu_eval_accuracy_moral_disputes": 0.4473684210526316,
8397
+ "mmlu_eval_accuracy_moral_scenarios": 0.23,
8398
+ "mmlu_eval_accuracy_nutrition": 0.6363636363636364,
8399
+ "mmlu_eval_accuracy_philosophy": 0.5,
8400
+ "mmlu_eval_accuracy_prehistory": 0.45714285714285713,
8401
+ "mmlu_eval_accuracy_professional_accounting": 0.22580645161290322,
8402
+ "mmlu_eval_accuracy_professional_law": 0.3176470588235294,
8403
+ "mmlu_eval_accuracy_professional_medicine": 0.4838709677419355,
8404
+ "mmlu_eval_accuracy_professional_psychology": 0.4927536231884058,
8405
+ "mmlu_eval_accuracy_public_relations": 0.5833333333333334,
8406
+ "mmlu_eval_accuracy_security_studies": 0.5555555555555556,
8407
+ "mmlu_eval_accuracy_sociology": 0.7272727272727273,
8408
+ "mmlu_eval_accuracy_us_foreign_policy": 0.7272727272727273,
8409
+ "mmlu_eval_accuracy_virology": 0.4444444444444444,
8410
+ "mmlu_eval_accuracy_world_religions": 0.7894736842105263,
8411
+ "mmlu_loss": 1.3744694253638892,
8412
+ "step": 8800
8413
+ },
8414
+ {
8415
+ "epoch": 3.99,
8416
+ "learning_rate": 0.0002,
8417
+ "loss": 0.7703,
8418
+ "step": 8810
8419
+ },
8420
+ {
8421
+ "epoch": 3.99,
8422
+ "learning_rate": 0.0002,
8423
+ "loss": 0.7679,
8424
+ "step": 8820
8425
+ },
8426
+ {
8427
+ "epoch": 4.0,
8428
+ "learning_rate": 0.0002,
8429
+ "loss": 0.7347,
8430
+ "step": 8830
8431
+ },
8432
+ {
8433
+ "epoch": 4.0,
8434
+ "learning_rate": 0.0002,
8435
+ "loss": 0.748,
8436
+ "step": 8840
8437
+ },
8438
+ {
8439
+ "epoch": 4.01,
8440
+ "learning_rate": 0.0002,
8441
+ "loss": 0.5329,
8442
+ "step": 8850
8443
+ },
8444
+ {
8445
+ "epoch": 4.01,
8446
+ "learning_rate": 0.0002,
8447
+ "loss": 0.5489,
8448
+ "step": 8860
8449
+ },
8450
+ {
8451
+ "epoch": 4.02,
8452
+ "learning_rate": 0.0002,
8453
+ "loss": 0.6205,
8454
+ "step": 8870
8455
+ },
8456
+ {
8457
+ "epoch": 4.02,
8458
+ "learning_rate": 0.0002,
8459
+ "loss": 0.6222,
8460
+ "step": 8880
8461
+ },
8462
+ {
8463
+ "epoch": 4.02,
8464
+ "learning_rate": 0.0002,
8465
+ "loss": 0.5869,
8466
+ "step": 8890
8467
+ },
8468
+ {
8469
+ "epoch": 4.03,
8470
+ "learning_rate": 0.0002,
8471
+ "loss": 0.6117,
8472
+ "step": 8900
8473
+ },
8474
+ {
8475
+ "epoch": 4.03,
8476
+ "learning_rate": 0.0002,
8477
+ "loss": 0.6009,
8478
+ "step": 8910
8479
+ },
8480
+ {
8481
+ "epoch": 4.04,
8482
+ "learning_rate": 0.0002,
8483
+ "loss": 0.5976,
8484
+ "step": 8920
8485
+ },
8486
+ {
8487
+ "epoch": 4.04,
8488
+ "learning_rate": 0.0002,
8489
+ "loss": 0.5355,
8490
+ "step": 8930
8491
+ },
8492
+ {
8493
+ "epoch": 4.05,
8494
+ "learning_rate": 0.0002,
8495
+ "loss": 0.6279,
8496
+ "step": 8940
8497
+ },
8498
+ {
8499
+ "epoch": 4.05,
8500
+ "learning_rate": 0.0002,
8501
+ "loss": 0.5849,
8502
+ "step": 8950
8503
+ },
8504
+ {
8505
+ "epoch": 4.06,
8506
+ "learning_rate": 0.0002,
8507
+ "loss": 0.6131,
8508
+ "step": 8960
8509
+ },
8510
+ {
8511
+ "epoch": 4.06,
8512
+ "learning_rate": 0.0002,
8513
+ "loss": 0.6033,
8514
+ "step": 8970
8515
+ },
8516
+ {
8517
+ "epoch": 4.07,
8518
+ "learning_rate": 0.0002,
8519
+ "loss": 0.5933,
8520
+ "step": 8980
8521
+ },
8522
+ {
8523
+ "epoch": 4.07,
8524
+ "learning_rate": 0.0002,
8525
+ "loss": 0.5611,
8526
+ "step": 8990
8527
+ },
8528
+ {
8529
+ "epoch": 4.07,
8530
+ "learning_rate": 0.0002,
8531
+ "loss": 0.542,
8532
+ "step": 9000
8533
+ },
8534
+ {
8535
+ "epoch": 4.07,
8536
+ "eval_loss": 1.1652448177337646,
8537
+ "eval_runtime": 131.9318,
8538
+ "eval_samples_per_second": 7.58,
8539
+ "eval_steps_per_second": 3.79,
8540
+ "step": 9000
8541
+ },
8542
+ {
8543
+ "epoch": 4.07,
8544
+ "mmlu_eval_accuracy": 0.509666668900527,
8545
+ "mmlu_eval_accuracy_abstract_algebra": 0.2727272727272727,
8546
+ "mmlu_eval_accuracy_anatomy": 0.6428571428571429,
8547
+ "mmlu_eval_accuracy_astronomy": 0.4375,
8548
+ "mmlu_eval_accuracy_business_ethics": 0.45454545454545453,
8549
+ "mmlu_eval_accuracy_clinical_knowledge": 0.5517241379310345,
8550
+ "mmlu_eval_accuracy_college_biology": 0.375,
8551
+ "mmlu_eval_accuracy_college_chemistry": 0.5,
8552
+ "mmlu_eval_accuracy_college_computer_science": 0.6363636363636364,
8553
+ "mmlu_eval_accuracy_college_mathematics": 0.2727272727272727,
8554
+ "mmlu_eval_accuracy_college_medicine": 0.36363636363636365,
8555
+ "mmlu_eval_accuracy_college_physics": 0.45454545454545453,
8556
+ "mmlu_eval_accuracy_computer_security": 0.36363636363636365,
8557
+ "mmlu_eval_accuracy_conceptual_physics": 0.5,
8558
+ "mmlu_eval_accuracy_econometrics": 0.16666666666666666,
8559
+ "mmlu_eval_accuracy_electrical_engineering": 0.4375,
8560
+ "mmlu_eval_accuracy_elementary_mathematics": 0.36585365853658536,
8561
+ "mmlu_eval_accuracy_formal_logic": 0.21428571428571427,
8562
+ "mmlu_eval_accuracy_global_facts": 0.5,
8563
+ "mmlu_eval_accuracy_high_school_biology": 0.46875,
8564
+ "mmlu_eval_accuracy_high_school_chemistry": 0.4090909090909091,
8565
+ "mmlu_eval_accuracy_high_school_computer_science": 0.5555555555555556,
8566
+ "mmlu_eval_accuracy_high_school_european_history": 0.7222222222222222,
8567
+ "mmlu_eval_accuracy_high_school_geography": 0.8636363636363636,
8568
+ "mmlu_eval_accuracy_high_school_government_and_politics": 0.5714285714285714,
8569
+ "mmlu_eval_accuracy_high_school_macroeconomics": 0.3953488372093023,
8570
+ "mmlu_eval_accuracy_high_school_mathematics": 0.20689655172413793,
8571
+ "mmlu_eval_accuracy_high_school_microeconomics": 0.5384615384615384,
8572
+ "mmlu_eval_accuracy_high_school_physics": 0.058823529411764705,
8573
+ "mmlu_eval_accuracy_high_school_psychology": 0.8333333333333334,
8574
+ "mmlu_eval_accuracy_high_school_statistics": 0.4782608695652174,
8575
+ "mmlu_eval_accuracy_high_school_us_history": 0.7727272727272727,
8576
+ "mmlu_eval_accuracy_high_school_world_history": 0.6153846153846154,
8577
+ "mmlu_eval_accuracy_human_aging": 0.7391304347826086,
8578
+ "mmlu_eval_accuracy_human_sexuality": 0.5,
8579
+ "mmlu_eval_accuracy_international_law": 0.7692307692307693,
8580
+ "mmlu_eval_accuracy_jurisprudence": 0.5454545454545454,
8581
+ "mmlu_eval_accuracy_logical_fallacies": 0.6111111111111112,
8582
+ "mmlu_eval_accuracy_machine_learning": 0.09090909090909091,
8583
+ "mmlu_eval_accuracy_management": 0.8181818181818182,
8584
+ "mmlu_eval_accuracy_marketing": 0.8,
8585
+ "mmlu_eval_accuracy_medical_genetics": 0.8181818181818182,
8586
+ "mmlu_eval_accuracy_miscellaneous": 0.627906976744186,
8587
+ "mmlu_eval_accuracy_moral_disputes": 0.47368421052631576,
8588
+ "mmlu_eval_accuracy_moral_scenarios": 0.23,
8589
+ "mmlu_eval_accuracy_nutrition": 0.6666666666666666,
8590
+ "mmlu_eval_accuracy_philosophy": 0.5,
8591
+ "mmlu_eval_accuracy_prehistory": 0.45714285714285713,
8592
+ "mmlu_eval_accuracy_professional_accounting": 0.2903225806451613,
8593
+ "mmlu_eval_accuracy_professional_law": 0.3176470588235294,
8594
+ "mmlu_eval_accuracy_professional_medicine": 0.5161290322580645,
8595
+ "mmlu_eval_accuracy_professional_psychology": 0.43478260869565216,
8596
+ "mmlu_eval_accuracy_public_relations": 0.5,
8597
+ "mmlu_eval_accuracy_security_studies": 0.5555555555555556,
8598
+ "mmlu_eval_accuracy_sociology": 0.7727272727272727,
8599
+ "mmlu_eval_accuracy_us_foreign_policy": 0.7272727272727273,
8600
+ "mmlu_eval_accuracy_virology": 0.5,
8601
+ "mmlu_eval_accuracy_world_religions": 0.7894736842105263,
8602
+ "mmlu_loss": 1.2733214086714364,
8603
+ "step": 9000
8604
+ },
8605
+ {
8606
+ "epoch": 4.08,
8607
+ "learning_rate": 0.0002,
8608
+ "loss": 0.5721,
8609
+ "step": 9010
8610
+ },
8611
+ {
8612
+ "epoch": 4.08,
8613
+ "learning_rate": 0.0002,
8614
+ "loss": 0.6447,
8615
+ "step": 9020
8616
+ },
8617
+ {
8618
+ "epoch": 4.09,
8619
+ "learning_rate": 0.0002,
8620
+ "loss": 0.6728,
8621
+ "step": 9030
8622
+ },
8623
+ {
8624
+ "epoch": 4.09,
8625
+ "learning_rate": 0.0002,
8626
+ "loss": 0.563,
8627
+ "step": 9040
8628
+ },
8629
+ {
8630
+ "epoch": 4.1,
8631
+ "learning_rate": 0.0002,
8632
+ "loss": 0.5142,
8633
+ "step": 9050
8634
+ },
8635
+ {
8636
+ "epoch": 4.1,
8637
+ "learning_rate": 0.0002,
8638
+ "loss": 0.5706,
8639
+ "step": 9060
8640
+ },
8641
+ {
8642
+ "epoch": 4.11,
8643
+ "learning_rate": 0.0002,
8644
+ "loss": 0.5645,
8645
+ "step": 9070
8646
+ },
8647
+ {
8648
+ "epoch": 4.11,
8649
+ "learning_rate": 0.0002,
8650
+ "loss": 0.6555,
8651
+ "step": 9080
8652
+ },
8653
+ {
8654
+ "epoch": 4.11,
8655
+ "learning_rate": 0.0002,
8656
+ "loss": 0.5631,
8657
+ "step": 9090
8658
+ },
8659
+ {
8660
+ "epoch": 4.12,
8661
+ "learning_rate": 0.0002,
8662
+ "loss": 0.5806,
8663
+ "step": 9100
8664
+ },
8665
+ {
8666
+ "epoch": 4.12,
8667
+ "learning_rate": 0.0002,
8668
+ "loss": 0.6276,
8669
+ "step": 9110
8670
+ },
8671
+ {
8672
+ "epoch": 4.13,
8673
+ "learning_rate": 0.0002,
8674
+ "loss": 0.6265,
8675
+ "step": 9120
8676
+ },
8677
+ {
8678
+ "epoch": 4.13,
8679
+ "learning_rate": 0.0002,
8680
+ "loss": 0.6139,
8681
+ "step": 9130
8682
+ },
8683
+ {
8684
+ "epoch": 4.14,
8685
+ "learning_rate": 0.0002,
8686
+ "loss": 0.624,
8687
+ "step": 9140
8688
+ },
8689
+ {
8690
+ "epoch": 4.14,
8691
+ "learning_rate": 0.0002,
8692
+ "loss": 0.6282,
8693
+ "step": 9150
8694
+ },
8695
+ {
8696
+ "epoch": 4.15,
8697
+ "learning_rate": 0.0002,
8698
+ "loss": 0.6077,
8699
+ "step": 9160
8700
+ },
8701
+ {
8702
+ "epoch": 4.15,
8703
+ "learning_rate": 0.0002,
8704
+ "loss": 0.5957,
8705
+ "step": 9170
8706
+ },
8707
+ {
8708
+ "epoch": 4.16,
8709
+ "learning_rate": 0.0002,
8710
+ "loss": 0.5802,
8711
+ "step": 9180
8712
+ },
8713
+ {
8714
+ "epoch": 4.16,
8715
+ "learning_rate": 0.0002,
8716
+ "loss": 0.5712,
8717
+ "step": 9190
8718
+ },
8719
+ {
8720
+ "epoch": 4.16,
8721
+ "learning_rate": 0.0002,
8722
+ "loss": 0.6209,
8723
+ "step": 9200
8724
+ },
8725
+ {
8726
+ "epoch": 4.16,
8727
+ "eval_loss": 1.16367506980896,
8728
+ "eval_runtime": 131.9956,
8729
+ "eval_samples_per_second": 7.576,
8730
+ "eval_steps_per_second": 3.788,
8731
+ "step": 9200
8732
+ },
8733
+ {
8734
+ "epoch": 4.16,
8735
+ "mmlu_eval_accuracy": 0.5090414754958608,
8736
+ "mmlu_eval_accuracy_abstract_algebra": 0.2727272727272727,
8737
+ "mmlu_eval_accuracy_anatomy": 0.5714285714285714,
8738
+ "mmlu_eval_accuracy_astronomy": 0.5,
8739
+ "mmlu_eval_accuracy_business_ethics": 0.45454545454545453,
8740
+ "mmlu_eval_accuracy_clinical_knowledge": 0.5862068965517241,
8741
+ "mmlu_eval_accuracy_college_biology": 0.375,
8742
+ "mmlu_eval_accuracy_college_chemistry": 0.25,
8743
+ "mmlu_eval_accuracy_college_computer_science": 0.6363636363636364,
8744
+ "mmlu_eval_accuracy_college_mathematics": 0.18181818181818182,
8745
+ "mmlu_eval_accuracy_college_medicine": 0.4090909090909091,
8746
+ "mmlu_eval_accuracy_college_physics": 0.45454545454545453,
8747
+ "mmlu_eval_accuracy_computer_security": 0.45454545454545453,
8748
+ "mmlu_eval_accuracy_conceptual_physics": 0.46153846153846156,
8749
+ "mmlu_eval_accuracy_econometrics": 0.3333333333333333,
8750
+ "mmlu_eval_accuracy_electrical_engineering": 0.375,
8751
+ "mmlu_eval_accuracy_elementary_mathematics": 0.3170731707317073,
8752
+ "mmlu_eval_accuracy_formal_logic": 0.21428571428571427,
8753
+ "mmlu_eval_accuracy_global_facts": 0.5,
8754
+ "mmlu_eval_accuracy_high_school_biology": 0.4375,
8755
+ "mmlu_eval_accuracy_high_school_chemistry": 0.45454545454545453,
8756
+ "mmlu_eval_accuracy_high_school_computer_science": 0.5555555555555556,
8757
+ "mmlu_eval_accuracy_high_school_european_history": 0.6111111111111112,
8758
+ "mmlu_eval_accuracy_high_school_geography": 0.8181818181818182,
8759
+ "mmlu_eval_accuracy_high_school_government_and_politics": 0.5714285714285714,
8760
+ "mmlu_eval_accuracy_high_school_macroeconomics": 0.46511627906976744,
8761
+ "mmlu_eval_accuracy_high_school_mathematics": 0.27586206896551724,
8762
+ "mmlu_eval_accuracy_high_school_microeconomics": 0.5384615384615384,
8763
+ "mmlu_eval_accuracy_high_school_physics": 0.11764705882352941,
8764
+ "mmlu_eval_accuracy_high_school_psychology": 0.8,
8765
+ "mmlu_eval_accuracy_high_school_statistics": 0.43478260869565216,
8766
+ "mmlu_eval_accuracy_high_school_us_history": 0.8181818181818182,
8767
+ "mmlu_eval_accuracy_high_school_world_history": 0.6153846153846154,
8768
+ "mmlu_eval_accuracy_human_aging": 0.7391304347826086,
8769
+ "mmlu_eval_accuracy_human_sexuality": 0.5,
8770
+ "mmlu_eval_accuracy_international_law": 0.8461538461538461,
8771
+ "mmlu_eval_accuracy_jurisprudence": 0.45454545454545453,
8772
+ "mmlu_eval_accuracy_logical_fallacies": 0.6111111111111112,
8773
+ "mmlu_eval_accuracy_machine_learning": 0.09090909090909091,
8774
+ "mmlu_eval_accuracy_management": 0.8181818181818182,
8775
+ "mmlu_eval_accuracy_marketing": 0.8,
8776
+ "mmlu_eval_accuracy_medical_genetics": 0.8181818181818182,
8777
+ "mmlu_eval_accuracy_miscellaneous": 0.6162790697674418,
8778
+ "mmlu_eval_accuracy_moral_disputes": 0.47368421052631576,
8779
+ "mmlu_eval_accuracy_moral_scenarios": 0.25,
8780
+ "mmlu_eval_accuracy_nutrition": 0.6363636363636364,
8781
+ "mmlu_eval_accuracy_philosophy": 0.5294117647058824,
8782
+ "mmlu_eval_accuracy_prehistory": 0.5142857142857142,
8783
+ "mmlu_eval_accuracy_professional_accounting": 0.3225806451612903,
8784
+ "mmlu_eval_accuracy_professional_law": 0.3352941176470588,
8785
+ "mmlu_eval_accuracy_professional_medicine": 0.5161290322580645,
8786
+ "mmlu_eval_accuracy_professional_psychology": 0.463768115942029,
8787
+ "mmlu_eval_accuracy_public_relations": 0.5,
8788
+ "mmlu_eval_accuracy_security_studies": 0.5185185185185185,
8789
+ "mmlu_eval_accuracy_sociology": 0.7272727272727273,
8790
+ "mmlu_eval_accuracy_us_foreign_policy": 0.7272727272727273,
8791
+ "mmlu_eval_accuracy_virology": 0.5555555555555556,
8792
+ "mmlu_eval_accuracy_world_religions": 0.7894736842105263,
8793
+ "mmlu_loss": 1.2645013554911702,
8794
+ "step": 9200
8795
+ },
8796
+ {
8797
+ "epoch": 4.17,
8798
+ "learning_rate": 0.0002,
8799
+ "loss": 0.6013,
8800
+ "step": 9210
8801
+ },
8802
+ {
8803
+ "epoch": 4.17,
8804
+ "learning_rate": 0.0002,
8805
+ "loss": 0.5758,
8806
+ "step": 9220
8807
+ },
8808
+ {
8809
+ "epoch": 4.18,
8810
+ "learning_rate": 0.0002,
8811
+ "loss": 0.6388,
8812
+ "step": 9230
8813
+ },
8814
+ {
8815
+ "epoch": 4.18,
8816
+ "learning_rate": 0.0002,
8817
+ "loss": 0.5835,
8818
+ "step": 9240
8819
+ },
8820
+ {
8821
+ "epoch": 4.19,
8822
+ "learning_rate": 0.0002,
8823
+ "loss": 0.666,
8824
+ "step": 9250
8825
+ },
8826
+ {
8827
+ "epoch": 4.19,
8828
+ "learning_rate": 0.0002,
8829
+ "loss": 0.5815,
8830
+ "step": 9260
8831
+ },
8832
+ {
8833
+ "epoch": 4.2,
8834
+ "learning_rate": 0.0002,
8835
+ "loss": 0.6212,
8836
+ "step": 9270
8837
+ },
8838
+ {
8839
+ "epoch": 4.2,
8840
+ "learning_rate": 0.0002,
8841
+ "loss": 0.6077,
8842
+ "step": 9280
8843
+ },
8844
+ {
8845
+ "epoch": 4.21,
8846
+ "learning_rate": 0.0002,
8847
+ "loss": 0.5915,
8848
+ "step": 9290
8849
+ },
8850
+ {
8851
+ "epoch": 4.21,
8852
+ "learning_rate": 0.0002,
8853
+ "loss": 0.6366,
8854
+ "step": 9300
8855
+ },
8856
+ {
8857
+ "epoch": 4.21,
8858
+ "learning_rate": 0.0002,
8859
+ "loss": 0.6262,
8860
+ "step": 9310
8861
+ },
8862
+ {
8863
+ "epoch": 4.22,
8864
+ "learning_rate": 0.0002,
8865
+ "loss": 0.6866,
8866
+ "step": 9320
8867
+ },
8868
+ {
8869
+ "epoch": 4.22,
8870
+ "learning_rate": 0.0002,
8871
+ "loss": 0.575,
8872
+ "step": 9330
8873
+ },
8874
+ {
8875
+ "epoch": 4.23,
8876
+ "learning_rate": 0.0002,
8877
+ "loss": 0.5461,
8878
+ "step": 9340
8879
+ },
8880
+ {
8881
+ "epoch": 4.23,
8882
+ "learning_rate": 0.0002,
8883
+ "loss": 0.5366,
8884
+ "step": 9350
8885
+ },
8886
+ {
8887
+ "epoch": 4.24,
8888
+ "learning_rate": 0.0002,
8889
+ "loss": 0.6316,
8890
+ "step": 9360
8891
+ },
8892
+ {
8893
+ "epoch": 4.24,
8894
+ "learning_rate": 0.0002,
8895
+ "loss": 0.5976,
8896
+ "step": 9370
8897
+ },
8898
+ {
8899
+ "epoch": 4.25,
8900
+ "learning_rate": 0.0002,
8901
+ "loss": 0.5686,
8902
+ "step": 9380
8903
+ },
8904
+ {
8905
+ "epoch": 4.25,
8906
+ "learning_rate": 0.0002,
8907
+ "loss": 0.5912,
8908
+ "step": 9390
8909
+ },
8910
+ {
8911
+ "epoch": 4.26,
8912
+ "learning_rate": 0.0002,
8913
+ "loss": 0.6469,
8914
+ "step": 9400
8915
+ },
8916
+ {
8917
+ "epoch": 4.26,
8918
+ "eval_loss": 1.1727190017700195,
8919
+ "eval_runtime": 131.9112,
8920
+ "eval_samples_per_second": 7.581,
8921
+ "eval_steps_per_second": 3.79,
8922
+ "step": 9400
8923
+ },
8924
+ {
8925
+ "epoch": 4.26,
8926
+ "mmlu_eval_accuracy": 0.4921093913412396,
8927
+ "mmlu_eval_accuracy_abstract_algebra": 0.2727272727272727,
8928
+ "mmlu_eval_accuracy_anatomy": 0.6428571428571429,
8929
+ "mmlu_eval_accuracy_astronomy": 0.5,
8930
+ "mmlu_eval_accuracy_business_ethics": 0.45454545454545453,
8931
+ "mmlu_eval_accuracy_clinical_knowledge": 0.5862068965517241,
8932
+ "mmlu_eval_accuracy_college_biology": 0.375,
8933
+ "mmlu_eval_accuracy_college_chemistry": 0.125,
8934
+ "mmlu_eval_accuracy_college_computer_science": 0.6363636363636364,
8935
+ "mmlu_eval_accuracy_college_mathematics": 0.18181818181818182,
8936
+ "mmlu_eval_accuracy_college_medicine": 0.3181818181818182,
8937
+ "mmlu_eval_accuracy_college_physics": 0.36363636363636365,
8938
+ "mmlu_eval_accuracy_computer_security": 0.45454545454545453,
8939
+ "mmlu_eval_accuracy_conceptual_physics": 0.5,
8940
+ "mmlu_eval_accuracy_econometrics": 0.25,
8941
+ "mmlu_eval_accuracy_electrical_engineering": 0.3125,
8942
+ "mmlu_eval_accuracy_elementary_mathematics": 0.34146341463414637,
8943
+ "mmlu_eval_accuracy_formal_logic": 0.14285714285714285,
8944
+ "mmlu_eval_accuracy_global_facts": 0.6,
8945
+ "mmlu_eval_accuracy_high_school_biology": 0.40625,
8946
+ "mmlu_eval_accuracy_high_school_chemistry": 0.45454545454545453,
8947
+ "mmlu_eval_accuracy_high_school_computer_science": 0.5555555555555556,
8948
+ "mmlu_eval_accuracy_high_school_european_history": 0.6111111111111112,
8949
+ "mmlu_eval_accuracy_high_school_geography": 0.8181818181818182,
8950
+ "mmlu_eval_accuracy_high_school_government_and_politics": 0.47619047619047616,
8951
+ "mmlu_eval_accuracy_high_school_macroeconomics": 0.37209302325581395,
8952
+ "mmlu_eval_accuracy_high_school_mathematics": 0.2413793103448276,
8953
+ "mmlu_eval_accuracy_high_school_microeconomics": 0.38461538461538464,
8954
+ "mmlu_eval_accuracy_high_school_physics": 0.17647058823529413,
8955
+ "mmlu_eval_accuracy_high_school_psychology": 0.8166666666666667,
8956
+ "mmlu_eval_accuracy_high_school_statistics": 0.43478260869565216,
8957
+ "mmlu_eval_accuracy_high_school_us_history": 0.7727272727272727,
8958
+ "mmlu_eval_accuracy_high_school_world_history": 0.6538461538461539,
8959
+ "mmlu_eval_accuracy_human_aging": 0.6956521739130435,
8960
+ "mmlu_eval_accuracy_human_sexuality": 0.4166666666666667,
8961
+ "mmlu_eval_accuracy_international_law": 0.8461538461538461,
8962
+ "mmlu_eval_accuracy_jurisprudence": 0.36363636363636365,
8963
+ "mmlu_eval_accuracy_logical_fallacies": 0.6111111111111112,
8964
+ "mmlu_eval_accuracy_machine_learning": 0.18181818181818182,
8965
+ "mmlu_eval_accuracy_management": 0.6363636363636364,
8966
+ "mmlu_eval_accuracy_marketing": 0.76,
8967
+ "mmlu_eval_accuracy_medical_genetics": 0.8181818181818182,
8968
+ "mmlu_eval_accuracy_miscellaneous": 0.6046511627906976,
8969
+ "mmlu_eval_accuracy_moral_disputes": 0.47368421052631576,
8970
+ "mmlu_eval_accuracy_moral_scenarios": 0.23,
8971
+ "mmlu_eval_accuracy_nutrition": 0.6363636363636364,
8972
+ "mmlu_eval_accuracy_philosophy": 0.5,
8973
+ "mmlu_eval_accuracy_prehistory": 0.4857142857142857,
8974
+ "mmlu_eval_accuracy_professional_accounting": 0.25806451612903225,
8975
+ "mmlu_eval_accuracy_professional_law": 0.32941176470588235,
8976
+ "mmlu_eval_accuracy_professional_medicine": 0.4838709677419355,
8977
+ "mmlu_eval_accuracy_professional_psychology": 0.4927536231884058,
8978
+ "mmlu_eval_accuracy_public_relations": 0.5833333333333334,
8979
+ "mmlu_eval_accuracy_security_studies": 0.5555555555555556,
8980
+ "mmlu_eval_accuracy_sociology": 0.7272727272727273,
8981
+ "mmlu_eval_accuracy_us_foreign_policy": 0.7272727272727273,
8982
+ "mmlu_eval_accuracy_virology": 0.6111111111111112,
8983
+ "mmlu_eval_accuracy_world_religions": 0.7894736842105263,
8984
+ "mmlu_loss": 1.3051679126198548,
8985
+ "step": 9400
8986
+ },
8987
+ {
8988
+ "epoch": 4.26,
8989
+ "learning_rate": 0.0002,
8990
+ "loss": 0.6171,
8991
+ "step": 9410
8992
+ },
8993
+ {
8994
+ "epoch": 4.26,
8995
+ "learning_rate": 0.0002,
8996
+ "loss": 0.6897,
8997
+ "step": 9420
8998
+ },
8999
+ {
9000
+ "epoch": 4.27,
9001
+ "learning_rate": 0.0002,
9002
+ "loss": 0.5739,
9003
+ "step": 9430
9004
+ },
9005
+ {
9006
+ "epoch": 4.27,
9007
+ "learning_rate": 0.0002,
9008
+ "loss": 0.6139,
9009
+ "step": 9440
9010
+ },
9011
+ {
9012
+ "epoch": 4.28,
9013
+ "learning_rate": 0.0002,
9014
+ "loss": 0.5933,
9015
+ "step": 9450
9016
+ },
9017
+ {
9018
+ "epoch": 4.28,
9019
+ "learning_rate": 0.0002,
9020
+ "loss": 0.6399,
9021
+ "step": 9460
9022
+ },
9023
+ {
9024
+ "epoch": 4.29,
9025
+ "learning_rate": 0.0002,
9026
+ "loss": 0.6395,
9027
+ "step": 9470
9028
+ },
9029
+ {
9030
+ "epoch": 4.29,
9031
+ "learning_rate": 0.0002,
9032
+ "loss": 0.5883,
9033
+ "step": 9480
9034
+ },
9035
+ {
9036
+ "epoch": 4.3,
9037
+ "learning_rate": 0.0002,
9038
+ "loss": 0.5722,
9039
+ "step": 9490
9040
+ },
9041
+ {
9042
+ "epoch": 4.3,
9043
+ "learning_rate": 0.0002,
9044
+ "loss": 0.5827,
9045
+ "step": 9500
9046
+ },
9047
+ {
9048
+ "epoch": 4.31,
9049
+ "learning_rate": 0.0002,
9050
+ "loss": 0.6559,
9051
+ "step": 9510
9052
+ },
9053
+ {
9054
+ "epoch": 4.31,
9055
+ "learning_rate": 0.0002,
9056
+ "loss": 0.5878,
9057
+ "step": 9520
9058
+ },
9059
+ {
9060
+ "epoch": 4.31,
9061
+ "learning_rate": 0.0002,
9062
+ "loss": 0.6313,
9063
+ "step": 9530
9064
+ },
9065
+ {
9066
+ "epoch": 4.32,
9067
+ "learning_rate": 0.0002,
9068
+ "loss": 0.6321,
9069
+ "step": 9540
9070
+ },
9071
+ {
9072
+ "epoch": 4.32,
9073
+ "learning_rate": 0.0002,
9074
+ "loss": 0.5942,
9075
+ "step": 9550
9076
+ },
9077
+ {
9078
+ "epoch": 4.33,
9079
+ "learning_rate": 0.0002,
9080
+ "loss": 0.5411,
9081
+ "step": 9560
9082
+ },
9083
+ {
9084
+ "epoch": 4.33,
9085
+ "learning_rate": 0.0002,
9086
+ "loss": 0.6178,
9087
+ "step": 9570
9088
+ },
9089
+ {
9090
+ "epoch": 4.34,
9091
+ "learning_rate": 0.0002,
9092
+ "loss": 0.6056,
9093
+ "step": 9580
9094
+ },
9095
+ {
9096
+ "epoch": 4.34,
9097
+ "learning_rate": 0.0002,
9098
+ "loss": 0.5937,
9099
+ "step": 9590
9100
+ },
9101
+ {
9102
+ "epoch": 4.35,
9103
+ "learning_rate": 0.0002,
9104
+ "loss": 0.6156,
9105
+ "step": 9600
9106
+ },
9107
+ {
9108
+ "epoch": 4.35,
9109
+ "eval_loss": 1.1685025691986084,
9110
+ "eval_runtime": 131.8007,
9111
+ "eval_samples_per_second": 7.587,
9112
+ "eval_steps_per_second": 3.794,
9113
+ "step": 9600
9114
+ },
9115
+ {
9116
+ "epoch": 4.35,
9117
+ "mmlu_eval_accuracy": 0.5008179785910191,
9118
+ "mmlu_eval_accuracy_abstract_algebra": 0.2727272727272727,
9119
+ "mmlu_eval_accuracy_anatomy": 0.6428571428571429,
9120
+ "mmlu_eval_accuracy_astronomy": 0.5,
9121
+ "mmlu_eval_accuracy_business_ethics": 0.45454545454545453,
9122
+ "mmlu_eval_accuracy_clinical_knowledge": 0.5862068965517241,
9123
+ "mmlu_eval_accuracy_college_biology": 0.375,
9124
+ "mmlu_eval_accuracy_college_chemistry": 0.125,
9125
+ "mmlu_eval_accuracy_college_computer_science": 0.6363636363636364,
9126
+ "mmlu_eval_accuracy_college_mathematics": 0.18181818181818182,
9127
+ "mmlu_eval_accuracy_college_medicine": 0.3181818181818182,
9128
+ "mmlu_eval_accuracy_college_physics": 0.45454545454545453,
9129
+ "mmlu_eval_accuracy_computer_security": 0.36363636363636365,
9130
+ "mmlu_eval_accuracy_conceptual_physics": 0.5,
9131
+ "mmlu_eval_accuracy_econometrics": 0.25,
9132
+ "mmlu_eval_accuracy_electrical_engineering": 0.4375,
9133
+ "mmlu_eval_accuracy_elementary_mathematics": 0.34146341463414637,
9134
+ "mmlu_eval_accuracy_formal_logic": 0.14285714285714285,
9135
+ "mmlu_eval_accuracy_global_facts": 0.5,
9136
+ "mmlu_eval_accuracy_high_school_biology": 0.46875,
9137
+ "mmlu_eval_accuracy_high_school_chemistry": 0.5,
9138
+ "mmlu_eval_accuracy_high_school_computer_science": 0.5555555555555556,
9139
+ "mmlu_eval_accuracy_high_school_european_history": 0.5555555555555556,
9140
+ "mmlu_eval_accuracy_high_school_geography": 0.8636363636363636,
9141
+ "mmlu_eval_accuracy_high_school_government_and_politics": 0.5714285714285714,
9142
+ "mmlu_eval_accuracy_high_school_macroeconomics": 0.4418604651162791,
9143
+ "mmlu_eval_accuracy_high_school_mathematics": 0.27586206896551724,
9144
+ "mmlu_eval_accuracy_high_school_microeconomics": 0.46153846153846156,
9145
+ "mmlu_eval_accuracy_high_school_physics": 0.11764705882352941,
9146
+ "mmlu_eval_accuracy_high_school_psychology": 0.85,
9147
+ "mmlu_eval_accuracy_high_school_statistics": 0.391304347826087,
9148
+ "mmlu_eval_accuracy_high_school_us_history": 0.7727272727272727,
9149
+ "mmlu_eval_accuracy_high_school_world_history": 0.6538461538461539,
9150
+ "mmlu_eval_accuracy_human_aging": 0.7391304347826086,
9151
+ "mmlu_eval_accuracy_human_sexuality": 0.4166666666666667,
9152
+ "mmlu_eval_accuracy_international_law": 0.8461538461538461,
9153
+ "mmlu_eval_accuracy_jurisprudence": 0.36363636363636365,
9154
+ "mmlu_eval_accuracy_logical_fallacies": 0.5555555555555556,
9155
+ "mmlu_eval_accuracy_machine_learning": 0.18181818181818182,
9156
+ "mmlu_eval_accuracy_management": 0.8181818181818182,
9157
+ "mmlu_eval_accuracy_marketing": 0.76,
9158
+ "mmlu_eval_accuracy_medical_genetics": 0.8181818181818182,
9159
+ "mmlu_eval_accuracy_miscellaneous": 0.6511627906976745,
9160
+ "mmlu_eval_accuracy_moral_disputes": 0.4473684210526316,
9161
+ "mmlu_eval_accuracy_moral_scenarios": 0.24,
9162
+ "mmlu_eval_accuracy_nutrition": 0.6363636363636364,
9163
+ "mmlu_eval_accuracy_philosophy": 0.5294117647058824,
9164
+ "mmlu_eval_accuracy_prehistory": 0.4857142857142857,
9165
+ "mmlu_eval_accuracy_professional_accounting": 0.3225806451612903,
9166
+ "mmlu_eval_accuracy_professional_law": 0.34705882352941175,
9167
+ "mmlu_eval_accuracy_professional_medicine": 0.45161290322580644,
9168
+ "mmlu_eval_accuracy_professional_psychology": 0.463768115942029,
9169
+ "mmlu_eval_accuracy_public_relations": 0.5833333333333334,
9170
+ "mmlu_eval_accuracy_security_studies": 0.5925925925925926,
9171
+ "mmlu_eval_accuracy_sociology": 0.7727272727272727,
9172
+ "mmlu_eval_accuracy_us_foreign_policy": 0.7272727272727273,
9173
+ "mmlu_eval_accuracy_virology": 0.4444444444444444,
9174
+ "mmlu_eval_accuracy_world_religions": 0.7894736842105263,
9175
+ "mmlu_loss": 1.2278708620069856,
9176
+ "step": 9600
9177
  }
9178
  ],
9179
  "max_steps": 10000,
9180
  "num_train_epochs": 5,
9181
+ "total_flos": 3.428933201958273e+18,
9182
  "trial_name": null,
9183
  "trial_params": null
9184
  }
{checkpoint-7600 → checkpoint-9600}/training_args.bin RENAMED
File without changes